{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Testing on validation data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Transforming the data" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import warnings\n", "warnings.filterwarnings('ignore')\n", "from tabulate import tabulate" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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labelsccracemaritalethnicgenderstateagePain severity - 0-10 verbal numeric rating [Score] - ReportedInfluenza seasonal injectable preservative free...Parainfluenza virus 1 RNA [Presence] in Respiratory specimen by NAA with probe detectionInfluenza virus B RNA [Presence] in Respiratory specimen by NAA with probe detectionInfluenza virus A RNA [Presence] in Respiratory specimen by NAA with probe detectionAdenovirus A+B+C+D+E DNA [Presence] in Respiratory specimen by NAA with probe detectionSARS-CoV-2 RNA Pnl Resp NAA+probeHydroxychloroquine Sulfate 200 MG Oral Tablet1 ML denosumab 60 MG/ML Prefilled SyringeFexofenadine hydrochloride 60 MG Oral TabletLeronlimab 700 MG InjectionLenzilumab 200 MG IV
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10100whitesnonhispanicfmassachusetts50t70abnormalTrue...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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5 rows × 783 columns

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" ], "text/plain": [ " label scc race marital ethnic gender state age \\\n", "0 0 113 white m hispanic m massachusetts 50t70 \n", "1 0 100 white s nonhispanic f massachusetts 50t70 \n", "2 0 106 other m nonhispanic f massachusetts 30t50 \n", "3 1 74 hawaiian m nonhispanic m massachusetts gt70 \n", "4 0 112 white m nonhispanic f massachusetts 50t70 \n", "\n", " Pain severity - 0-10 verbal numeric rating [Score] - Reported \\\n", "0 abnormal \n", "1 abnormal \n", "2 normal \n", "3 abnormal \n", "4 abnormal \n", "\n", " Influenza seasonal injectable preservative free ... \\\n", "0 True ... \n", "1 True ... \n", "2 True ... \n", "3 True ... \n", "4 True ... \n", "\n", " Parainfluenza virus 1 RNA [Presence] in Respiratory specimen by NAA with probe detection \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " Influenza virus B RNA [Presence] in Respiratory specimen by NAA with probe detection \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " Influenza virus A RNA [Presence] in Respiratory specimen by NAA with probe detection \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " Adenovirus A+B+C+D+E DNA [Presence] in Respiratory specimen by NAA with probe detection \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " SARS-CoV-2 RNA Pnl Resp NAA+probe \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " Hydroxychloroquine Sulfate 200 MG Oral Tablet \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " 1 ML denosumab 60 MG/ML Prefilled Syringe \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " Fexofenadine hydrochloride 60 MG Oral Tablet Leronlimab 700 MG Injection \\\n", "0 NaN NaN \n", "1 NaN NaN \n", "2 NaN NaN \n", "3 NaN NaN \n", "4 NaN NaN \n", "\n", " Lenzilumab 200 MG IV \n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", "[5 rows x 783 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = pd.read_csv('../validation_data/validation_data.csv')\n", "df = df.drop('ptnum', axis=1)\n", "df.drop(columns=['C-20565-8'], inplace=True)\n", "df_codes = pd.read_csv('../data/codes.csv')\n", "code_to_name = df_codes.set_index('code')['name'].to_dict()\n", "df = df.rename(columns=code_to_name)\n", "df2 = df.copy()\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "DataFrame after combining columns with the same name:\n", " Screening for domestic abuse (procedure) Osteoporosis (disorder) \\\n", "0 True NaN \n", "1 True NaN \n", "2 True NaN \n", "3 True NaN \n", "4 True NaN \n", "... ... ... \n", "3874 True True \n", "3875 NaN NaN \n", "3876 True NaN \n", "3877 True NaN \n", "3878 True NaN \n", "\n", " Asthma screening \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "... ... \n", "3874 NaN \n", "3875 NaN \n", "3876 NaN \n", "3877 NaN \n", "3878 NaN \n", "\n", " Influenza virus B RNA [Presence] in Respiratory specimen by NAA with probe detection \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "... ... \n", "3874 NaN \n", "3875 NaN \n", "3876 NaN \n", "3877 NaN \n", "3878 NaN \n", "\n", " Appearance of Urine 1 ML Enoxaparin sodium 150 MG/ML Prefilled Syringe \\\n", "0 NaN NaN \n", "1 NaN NaN \n", "2 NaN NaN \n", "3 NaN NaN \n", "4 NaN NaN \n", "... ... ... \n", "3874 NaN NaN \n", "3875 cloudy NaN \n", "3876 NaN NaN \n", "3877 NaN NaN \n", "3878 NaN NaN \n", "\n", " Brief general examination (procedure) letrozole 2.5 MG Oral Tablet \\\n", "0 NaN NaN \n", "1 NaN NaN \n", "2 NaN NaN \n", "3 NaN NaN \n", "4 NaN NaN \n", "... ... ... \n", "3874 NaN NaN \n", "3875 NaN NaN \n", "3876 NaN NaN \n", "3877 NaN NaN \n", "3878 True NaN \n", "\n", " SARS-CoV-2 RNA Pnl Resp NAA+probe Limited social contact (finding) ... \\\n", "0 NaN True ... \n", "1 NaN True ... \n", "2 NaN True ... \n", "3 NaN NaN ... \n", "4 NaN True ... \n", "... ... ... ... \n", "3874 NaN True ... \n", "3875 NaN NaN ... \n", "3876 NaN NaN ... \n", "3877 NaN True ... \n", "3878 NaN True ... \n", "\n", " Chlorpheniramine Maleate 4 MG Oral Tablet \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "... ... \n", "3874 NaN \n", "3875 NaN \n", "3876 NaN \n", "3877 NaN \n", "3878 NaN \n", "\n", " Drugs of abuse 5 panel - Urine by Screen method \\\n", "0 NaN \n", "1 NaN \n", "2 negative \n", "3 NaN \n", "4 NaN \n", "... ... \n", "3874 NaN \n", "3875 NaN \n", "3876 NaN \n", "3877 NaN \n", "3878 NaN \n", "\n", " Admission to neurosurgical department 20 Gene mutation test \\\n", "0 NaN NaN \n", "1 NaN NaN \n", "2 NaN NaN \n", "3 NaN NaN \n", "4 NaN NaN \n", "... ... ... \n", "3874 NaN NaN \n", "3875 NaN NaN \n", "3876 NaN NaN \n", "3877 NaN NaN \n", "3878 NaN NaN \n", "\n", " Abuse-Deterrent 12 HR Oxycodone Hydrochloride 15 MG Extended Release Oral Tablet \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "... ... \n", "3874 True \n", "3875 NaN \n", "3876 NaN \n", "3877 NaN \n", "3878 NaN \n", "\n", " Sputum examination (procedure) carvedilol 25 MG Oral Tablet \\\n", "0 NaN NaN \n", "1 NaN NaN \n", "2 NaN NaN \n", "3 NaN NaN \n", "4 NaN NaN \n", "... ... ... \n", "3874 NaN NaN \n", "3875 NaN NaN \n", "3876 NaN NaN \n", "3877 NaN True \n", "3878 NaN NaN \n", "\n", " Terfenadine 60 MG Oral Tablet Removal of endotracheal tube (procedure) \\\n", "0 NaN NaN \n", "1 NaN NaN \n", "2 NaN NaN \n", "3 NaN NaN \n", "4 NaN NaN \n", "... ... ... \n", "3874 NaN NaN \n", "3875 NaN NaN \n", "3876 NaN NaN \n", "3877 NaN NaN \n", "3878 NaN NaN \n", "\n", " Abuse-Deterrent 12 HR Oxycodone Hydrochloride 10 MG Extended Release Oral Tablet [Oxycontin] \n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "... ... \n", "3874 NaN \n", "3875 NaN \n", "3876 NaN \n", "3877 NaN \n", "3878 NaN \n", "\n", "[3879 rows x 779 columns]\n" ] } ], "source": [ "columns = df.columns\n", "unique_columns = list(set(columns)) # Get unique column names\n", "\n", "# Create a new DataFrame with combined columns\n", "df_combined = pd.DataFrame()\n", "\n", "# Iterate over the unique columns to combine and merge appropriately\n", "for col in unique_columns:\n", " if list(columns).count(col) > 1: # If the column name is duplicated\n", " # Find all columns with this name and combine them, e.g., with first non-null\n", " combined_series = df[[col]].bfill(axis=1).iloc[:, 0] # Backfill to combine\n", " df_combined[col] = combined_series\n", " else:\n", " df_combined[col] = df[col] # If it's unique, just copy the column\n", "\n", "print(\"\\nDataFrame after combining columns with the same name:\")\n", "print(df_combined)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "df2 = df_combined.copy()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "category_dict = {}" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "respiratory_disorders_columns = [\n", " 'Acute bacterial sinusitis (disorder)',\n", " 'Acute bronchitis (disorder)',\n", " 'Acute respiratory distress syndrome (disorder)',\n", " 'Acute viral pharyngitis (disorder)',\n", " 'Asthma',\n", " 'Asthma screening',\n", " 'Bacterial infectious disease (disorder)',\n", " 'COVID-19',\n", " 'Chronic obstructive bronchitis (disorder)',\n", " 'Cough (finding)',\n", " 'Dyspnea (finding)',\n", " 'Fever (finding)',\n", " 'Hemoptysis (finding)',\n", " 'Hypoxemia (disorder)',\n", " 'Influenza virus A Ag [Presence] in Nasopharynx by Rapid immunoassay',\n", " 'Influenza virus B Ag [Presence] in Nasopharynx by Rapid immunoassay',\n", " 'Measurement of respiratory function (procedure)',\n", " 'NDA020503 200 ACTUAT Albuterol 0.09 MG/ACTUAT Metered Dose Inhaler',\n", " 'Nasal congestion (finding)',\n", " 'Nasal sinus endoscopy (procedure)',\n", " 'Otitis media',\n", " 'Oxygen Therapy',\n", " 'Parainfluenza virus 3 RNA [Presence] in Respiratory specimen by NAA with probe detection',\n", " 'Pneumococcal conjugate PCV 13',\n", " 'Pneumonia (disorder)',\n", " 'Pulmonary emphysema (disorder)',\n", " 'Respiratory distress (finding)',\n", " 'SARS-CoV-2 RNA Pnl Resp NAA+probe',\n", " 'Sore throat symptom (finding)',\n", " 'Sputum examination (procedure)',\n", " 'Sputum finding (finding)',\n", " 'Streptococcal sore throat (disorder)',\n", " 'Streptococcus pneumoniae group B antigen test',\n", " 'Throat culture (procedure)',\n", " 'Total knee replacement',\n", " 'Transfer to stepdown unit (procedure)',\n", " 'Transplant of lung (procedure)',\n", " 'Viral sinusitis (disorder)',\n", " 'House dust mite (organism)',\n", " 'Mold (organism)',\n", " 'Grass pollen (substance)',\n", " 'Tree pollen (substance)',\n", " 'Animal dander (substance)',\n", " 'Wheezing (finding)'\n", "]\n", "\n", "\n", "df2['Respiratory Disorders'] = df2[respiratory_disorders_columns].sum(axis=1)\n", "category_dict['Respiratory Disorders'] = respiratory_disorders_columns" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "heart_and_cardiovascular_diseases_columns = [\n", " 'Acute deep venous thrombosis (disorder)',\n", " 'Acute pulmonary embolism (disorder)',\n", " 'Atrial Fibrillation',\n", " 'Blindness due to type 2 diabetes mellitus (disorder)',\n", " 'Chronic congestive heart failure (disorder)',\n", " 'Coronary Heart Disease',\n", " 'Diabetes',\n", " 'Diabetic renal disease (disorder)',\n", " 'Diabetic retinopathy associated with type II diabetes mellitus (disorder)',\n", " 'Hyperglycemia (disorder)',\n", " 'Hypertension',\n", " 'Hyperlipidemia',\n", " 'Hypertriglyceridemia (disorder)',\n", " 'Myocardial Infarction',\n", " 'Stroke',\n", " 'Heart failure (disorder)'\n", "]\n", "\n", "\n", "df2['Heart and Cardiovascular Diseases'] = df2[heart_and_cardiovascular_diseases_columns].sum(axis=1)\n", "category_dict['Heart and Cardiovascular Diseases'] = heart_and_cardiovascular_diseases_columns" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "metabolic_and_endocrine_disorders_columns = [\n", " 'Alcoholism',\n", " 'Anemia (disorder)',\n", " 'Body mass index 30+ - obesity (finding)',\n", " 'Chronic kidney disease stage 1 (disorder)',\n", " 'Chronic kidney disease stage 2 (disorder)',\n", " 'Chronic kidney disease stage 3 (disorder)',\n", " 'Fatigue (finding)',\n", " 'Gout',\n", " 'Hyperlipidemia',\n", " 'Hypertension',\n", " 'Hypertriglyceridemia (disorder)',\n", " 'Hypoxemia (disorder)',\n", " 'Idiopathic atrophic hypothyroidism',\n", " 'Loss of taste (finding)',\n", " 'Macular edema and retinopathy due to type 2 diabetes mellitus (disorder)',\n", " 'Metabolic syndrome X (disorder)',\n", " 'Microalbuminuria due to type 2 diabetes mellitus (disorder)',\n", " 'Neuropathy due to type 2 diabetes mellitus (disorder)',\n", " 'Nonproliferative diabetic retinopathy due to type 2 diabetes mellitus (disorder)',\n", " 'Osteoarthritis of hip',\n", " 'Osteoarthritis of knee',\n", " 'Osteoporosis (disorder)',\n", " 'Pathological fracture due to osteoporosis (disorder)',\n", " 'Prediabetes',\n", " 'Proteinuria due to type 2 diabetes mellitus (disorder)',\n", " 'Protracted diarrhea',\n", " 'Rheumatoid arthritis',\n", " 'Secondary malignant neoplasm of colon',\n", " 'Stress (finding)',\n", " 'Unhealthy alcohol drinking behavior (finding)',\n", " 'Whiplash injury to neck',\n", " 'Proliferative diabetic retinopathy due to type II diabetes mellitus (disorder)'\n", "]\n", "\n", "df2['Metabolic and Endocrine Disorders'] = df2[metabolic_and_endocrine_disorders_columns].sum(axis=1)\n", "category_dict['Metabolic and Endocrine Disorders'] = metabolic_and_endocrine_disorders_columns" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "neurological_disorders_columns = [\n", " 'Alzheimer\\'s disease (disorder)',\n", " 'Brain damage - traumatic',\n", " 'Chronic intractable migraine without aura',\n", " 'Chronic low back pain (finding)',\n", " 'Chronic neck pain (finding)',\n", " 'Chronic pain',\n", " 'Chronic paralysis due to lesion of spinal cord',\n", " 'Chronic sinusitis (disorder)',\n", " 'Epilepsy',\n", " 'Familial Alzheimer\\'s disease of early onset (disorder)',\n", " 'Fibromyalgia (disorder)',\n", " 'Lupus erythematosus',\n", " 'Male infertility due to cystic fibrosis (disorder)',\n", " 'Malignant neoplasm of breast (disorder)',\n", " 'Malignant tumor of colon',\n", " 'Seizure disorder',\n", " 'Sepsis (disorder)',\n", " 'Sepsis caused by virus (disorder)',\n", " 'Septic shock (disorder)',\n", " 'Shock (disorder)',\n", " 'Sinusitis (disorder)',\n", " 'Streptococcal sore throat (disorder)',\n", " 'Suspected COVID-19',\n", " 'Transformed migraine (disorder)',\n", " 'Victim of intimate partner abuse (finding)',\n", " 'Viral sinusitis (disorder)',\n", " 'Seizure Count Cerebral Cortex Electroencephalogram (EEG)',\n", " 'Headache (finding)',\n", " 'Primary fibromyalgia syndrome'\n", "]\n", "\n", "\n", "df2['Neurological Disorders'] = df2[neurological_disorders_columns].sum(axis=1)\n", "category_dict['Neurological Disorders'] = neurological_disorders_columns" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "orthopedic_injuries_columns = [\n", " 'Admission to orthopedic department',\n", " 'Ankle X-ray',\n", " 'Bone immobilization',\n", " 'Brain damage - traumatic',\n", " 'Bullet wound',\n", " 'Burn injury(morphologic abnormality)',\n", " 'Chronic kidney disease stage 1 (disorder)',\n", " 'Clavicle X-ray',\n", " 'Closed fracture of hip',\n", " 'Concussion injury of brain',\n", " 'Concussion with loss of consciousness',\n", " 'Concussion with no loss of consciousness',\n", " 'Facial laceration',\n", " 'Fracture of ankle',\n", " 'Fracture of clavicle',\n", " 'Fracture of forearm',\n", " 'Fracture of rib',\n", " 'Fracture of the vertebral column with spinal cord injury',\n", " 'Fracture of vertebral column without spinal cord injury',\n", " 'Fracture subluxation of wrist',\n", " 'History of amputation of foot (situation)',\n", " 'History of lower limb amputation (situation)',\n", " 'Hypertriglyceridemia (disorder)',\n", " 'Impacted molars',\n", " 'Injury of anterior cruciate ligament',\n", " 'Injury of heart (disorder)',\n", " 'Injury of kidney (disorder)',\n", " 'Injury of medial collateral ligament of knee',\n", " 'Injury of tendon of the rotator cuff of shoulder',\n", " 'Joint pain (finding)',\n", " 'Laceration of foot',\n", " 'Laceration of hand',\n", " 'Laceration of thigh',\n", " 'Localized primary osteoarthritis of the hand',\n", " 'Muscle pain (finding)',\n", " 'Rupture of appendix',\n", " 'Rupture of patellar tendon',\n", " 'Second degree burn',\n", " 'Sprain of ankle',\n", " 'Sprain of wrist',\n", " 'Surgical manipulation of joint of knee',\n", " 'Surgical manipulation of shoulder joint',\n", " 'Tear of meniscus of knee',\n", " 'Total knee replacement',\n", " 'Whiplash injury to neck',\n", " 'Third degree burn'\n", "]\n", "\n", "\n", "df2[\"Orthopedic Injuries\"] = df2[orthopedic_injuries_columns].sum(axis=1)\n", "category_dict['Orthopedic Injuries'] = orthopedic_injuries_columns" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "mental_health_columns = [\n", " 'Alcoholism',\n", " 'At risk for suicide (finding)',\n", " 'Brief general examination (procedure)',\n", " 'Care regimes assessment (procedure)',\n", " 'Comprehensive interview and evaluation (procedure)',\n", " 'Concussion with no loss of consciousness',\n", " 'Depression screening (procedure)',\n", " 'Depression screening using Patient Health Questionnaire Nine Item score (procedure)',\n", " 'Depression screening using Patient Health Questionnaire Two-Item score (procedure)',\n", " 'Died in hospice (finding)',\n", " 'Drug overdose',\n", " 'Evaluation of psychiatric state of patient',\n", " 'Has a criminal record (finding)',\n", " 'Homeless (finding)',\n", " 'Limited social contact (finding)',\n", " 'Mental health Outpatient Note',\n", " 'Mental health Telehealth Note',\n", " 'Mental health screening (procedure)',\n", " 'Misuses drugs (finding)',\n", " 'Nausea (finding)',\n", " 'Not in labor force (finding)',\n", " 'Part-time employment (finding)',\n", " 'Passive conjunctival congestion (finding)',\n", " 'Posttraumatic stress disorder',\n", " 'Psychiatric follow-up',\n", " 'Refugee (person)',\n", " 'Reports of violence in the environment (finding)',\n", " 'Severe anxiety (panic) (finding',\n", " 'Social isolation (finding)',\n", " 'Stress (finding)',\n", " 'Suicide risk assessment (procedure)',\n", " 'Victim of intimate partner abuse (finding)',\n", " 'Attempted suicide - cut/stab',\n", " 'Attempted suicide - suffocation',\n", " 'Opioid abuse (disorder)',\n", " 'Assessment of anxiety (procedure)'\n", "]\n", "\n", "\n", "df2['Mental Health'] = df2[mental_health_columns].sum(axis=1)\n", "category_dict['Mental Health'] = mental_health_columns" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "reproductive_and_pregancy_columns = [\n", " '1 ML medroxyPROGESTERone acetate 150 MG/ML Injection',\n", " '168 HR Ethinyl Estradiol 0.00146 MG/HR / norelgestromin 0.00625 MG/HR Transdermal System',\n", " 'Antenatal RhD antibody screening',\n", " 'Antepartum eclampsia',\n", " 'Augmentation of labor',\n", " 'Auscultation of the fetal heart',\n", " 'Bilateral tubal ligation',\n", " 'Blighted ovum',\n", " 'Camila 28 Day Pack',\n", " 'Counseling for termination of pregnancy',\n", " 'Cytopathology procedure preparation of smear genital source',\n", " 'Episiotomy',\n", " 'Errin 28 Day Pack',\n", " 'Estrostep Fe 28 Day Pack',\n", " 'Etonogestrel 68 MG Drug Implant',\n", " 'Evaluation of uterine fundal height',\n", " 'Excision of fallopian tube and surgical removal of ectopic pregnancy',\n", " 'Fetal anatomy study',\n", " 'Fetus with unknown complication',\n", " 'Gonorrhea infection test',\n", " 'Hyperlipidemia',\n", " 'Induced termination of pregnancy',\n", " 'Insertion of intrauterine contraceptive device',\n", " 'Insertion of subcutaneous contraceptive',\n", " 'Instrumental delivery',\n", " 'Jolivette 28 Day Pack',\n", " 'Kyleena 19.5 MG Intrauterine System',\n", " 'Leronlimab 700 MG Injection',\n", " 'Levonorgestrel 0.00354 MG/HR Drug Implant',\n", " 'Levora 0.15/30 28 Day Pack',\n", " 'Liletta 52 MG Intrauterine System',\n", " 'Medical induction of labor',\n", " 'Mestranol / Norethynodrel [Enovid]',\n", " 'Methotrexate injection into tubal pregnancy',\n", " 'Mirena 52 MG Intrauterine System',\n", " 'Miscarriage in first trimester',\n", " 'Natazia 28 Day Pack',\n", " 'Norinyl 1+50 28 Day Pack',\n", " 'NuvaRing 0.12/0.015 MG per 24HR 21 Day Vaginal Ring',\n", " 'Ortho Tri-Cyclen 28 Day Pack',\n", " 'Preeclampsia',\n", " 'Pregnancy termination care',\n", " 'Premature birth of newborn',\n", " 'Removal of intrauterine device',\n", " 'Removal of subcutaneous contraceptive',\n", " 'Replacement of contraceptive intrauterine device',\n", " 'RhD passive immunization',\n", " 'Screening for chromosomal aneuploidy in prenatal amniotic fluid',\n", " 'Spontaneous breech delivery',\n", " 'Standard pregnancy test',\n", " 'Tubal pregnancy',\n", " 'Ultrasonography of abdomen right upper quadrant and epigastrium',\n", " 'Ultrasonography of bilateral breasts (procedure)',\n", " 'Ultrasound scan for fetal viability',\n", " 'Vaccination for diphtheria pertussis and tetanus',\n", " 'Vasectomy' \n", "]\n", "\n", "df2['Reproductive and Pregnancy'] = df2[reproductive_and_pregancy_columns].sum(axis=1)\n", "category_dict['Reproductive and Pregnancy'] = reproductive_and_pregancy_columns" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "pain_relievers_and_analesics_columns = [\n", " '10 ML Alfentanil 0.5 MG/ML Injection',\n", " '10 ML Fentanyl 0.05 MG/ML Injection',\n", " '12 HR Hydrocodone Bitartrate 10 MG Extended Release Oral Capsule',\n", " '5 ML SUFentanil 0.05 MG/ML Injection',\n", " '72 HR Fentanyl 0.025 MG/HR Transdermal System',\n", " 'Abuse-Deterrent 12 HR Oxycodone Hydrochloride 10 MG Extended Release Oral Tablet [Oxycontin]',\n", " 'Abuse-Deterrent 12 HR Oxycodone Hydrochloride 15 MG Extended Release Oral Tablet',\n", " 'Acetaminophen 325 MG / oxyCODONE Hydrochloride 2.5 MG Oral Tablet',\n", " 'Acetaminophen 325 MG / oxyCODONE Hydrochloride 5 MG Oral Tablet',\n", " 'Acetaminophen 500 MG Oral Tablet',\n", " 'Acetaminophen 300 MG / Hydrocodone Bitartrate 5 MG Oral Tablet',\n", " 'Acetaminophen 325 MG / HYDROcodone Bitartrate 7.5 MG Oral Tablet',\n", " 'Acetaminophen 325 MG / Oxycodone Hydrochloride 10 MG Oral Tablet [Percocet]',\n", " 'Acetaminophen 325 MG Oral Tablet',\n", " 'Acetaminophen/Hydrocodone',\n", " 'Aspirin',\n", " 'Aspirin 81 MG Oral Tablet',\n", " 'Carbamazepine[Tegretol]',\n", " 'Chlorpheniramine Maleate 4 MG Oral Tablet',\n", " 'Clopidogrel 75 MG Oral Tablet',\n", " 'Colchicine 0.6 MG Oral Tablet',\n", " 'Cyclophosphamide 1000 MG Injection',\n", " 'Diazepam 5 MG Oral Tablet',\n", " 'Diazepam 5 MG/ML Injectable Solution',\n", " 'Doxycycline Monohydrate 100 MG Oral Tablet',\n", " 'Ibuprofen',\n", " 'Ibuprofen 200 MG Oral Tablet',\n", " 'Ibuprofen 400 MG Oral Tablet [Ibu]',\n", " 'Lorazepam 2 MG/ML Injectable Solution',\n", " 'Meperidine Hydrochloride 50 MG Oral Tablet',\n", " 'Muscle pain (finding)',\n", " 'Naproxen 500 MG Oral Tablet',\n", " 'Naproxen sodium 220 MG Oral Tablet',\n", " 'Nitroglycerin 0.4 MG/ACTUAT Mucosal Spray',\n", " 'Phenazopyridine hydrochloride 100 MG Oral Tablet',\n", " 'Sulfamethoxazole / Trimethoprim',\n", " 'buprenorphine 2 MG / naloxone 0.5 MG Sublingual Tablet',\n", " 'diphenhydrAMINE Hydrochloride 25 MG Oral Tablet',\n", " 'duloxetine 20 MG Delayed Release Oral Capsule',\n", " 'methadone hydrochloride 10 MG Oral Tablet',\n", " 'tramadol hydrochloride 50 MG Oral Tablet',\n", " 'clonazePAM 0.25 MG Oral Tablet',\n", " 'Midazolam 1 MG/ML Injectable Solution',\n", " 'Rocuronium bromide 10 MG/ML Injectable Solution',\n", " 'Epidural anesthesia',\n", "]\n", "\n", "\n", "df2['Pain Relievers and Analesics'] = df2[pain_relievers_and_analesics_columns].sum(axis=1)\n", "category_dict['Pain Relievers and Analesics'] = pain_relievers_and_analesics_columns" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "cardiovascular_and_blood_pressure_medications_columns = [\n", " '0.3 ML Enoxaparin sodium 100 MG/ML Prefilled Syringe',\n", " '0.4 ML Enoxaparin sodium 100 MG/ML Prefilled Syringe',\n", " '1 ML Enoxaparin sodium 150 MG/ML Prefilled Syringe',\n", " '1 ML heparin sodium porcine 5000 UNT/ML Injection',\n", " '3 ML Amiodarone hydrocholoride 50 MG/ML Prefilled Syringe',\n", " '4 ML norepinephrine 1 MG/ML Injection',\n", " 'Acute deep venous thrombosis (disorder)',\n", " 'Acute pulmonary embolism (disorder)',\n", " 'Alkaline phosphatase [Enzymatic activity/volume] in Serum or Plasma',\n", " 'Alteplase 100 MG Injection',\n", " 'Assessment using New York Heart Association Classification (procedure)',\n", " 'Atorvastatin 80 MG Oral Tablet',\n", " 'Atropine Sulfate 1 MG/ML Injectable Solution',\n", " 'Captopril 25 MG Oral Tablet',\n", " 'Carbon dioxide [Partial pressure] in Arterial blood',\n", " 'Cardiac Arrest',\n", " 'Cardiovascular stress testing (procedure)',\n", " 'Catheter ablation of tissue of heart',\n", " 'Coronary artery bypass grafting',\n", " 'Digoxin 0.125 MG Oral Tablet',\n", " 'Echocardiography (procedure)',\n", " 'Electrical cardioversion',\n", " 'Electrocardiographic procedure',\n", " 'Furosemide 40 MG Oral Tablet',\n", " 'Glomerular filtration rate/1.73 sq M.predicted',\n", " 'Heart rate',\n", " 'History of myocardial infarction (situation)',\n", " 'Hydrochlorothiazide 25 MG Oral Tablet',\n", " 'Implantation of left ventricular assist device (procedure)',\n", " 'Insertion of biventricular implantable cardioverter defibrillator',\n", " 'Lisinopril',\n", " 'Low Density Lipoprotein Cholesterol',\n", " 'Myocardial Infarction',\n", " 'Nitrofurantoin 5 MG/ML Oral Suspension',\n", " 'Peripheral blood smear interpretation',\n", " 'Referral to hypertension clinic',\n", " 'Shock (disorder)',\n", " 'Stroke',\n", " 'Transplantation of heart (procedure)',\n", " 'Verapamil Hydrochloride 40 MG',\n", " 'Warfarin Sodium 5 MG Oral Tablet',\n", " 'carvedilol 25 MG Oral Tablet',\n", " 'lisinopril 10 MG Oral Tablet',\n", " 'lisinopril 20 MG Oral Tablet',\n", " 'losartan potassium 25 MG Oral Tablet',\n", " 'losartan potassium 50 MG Oral Tablet',\n", " 'sacubitril 97 MG / valsartan 103 MG Oral Tablet',\n", " 'remifentanil 2 MG Injection',\n", " 'pregabalin 100 MG Oral Capsule'\n", "]\n", "\n", "\n", "df2['Cardiovascular and Blood Pressure'] = df2[cardiovascular_and_blood_pressure_medications_columns].sum(axis=1)\n", "category_dict['Cardiovascular and Blood Pressure'] = cardiovascular_and_blood_pressure_medications_columns" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "injection_medications_columns = [\n", " '10 ML Doxorubicin Hydrochloride 2 MG/ML Injection',\n", " '10 ML oxaliplatin 5 MG/ML Injection',\n", " '1 ML DOCEtaxel 20 MG/ML Injection',\n", " '1 ML Epinephrine 1 MG/ML Injection',\n", " '1 ML Morphine Sulfate 5 MG/ML Injection',\n", " '1 ML Vasopressin (USP) 20 UNT/ML Injection',\n", " '10 ML Fluorouracil 50 MG/ML Injection',\n", " '10 ML Pamidronate Disodium 3 MG/ML Injection',\n", " '100 ML Epirubicin Hydrochloride 2 MG/ML Injection',\n", " '100 ML Propofol 10 MG/ML Injection',\n", " '100 ML zoledronic acid 0.04 MG/ML Injection',\n", " '150 ML vancomycin 5 MG/ML Injection',\n", " '2 ML Ondansetron 2 MG/ML Injection',\n", " '20 ML tocilizumab 20 MG/ML Injection',\n", " '5 ML hyaluronidase-oysk 2000 UNT/ML / trastuzumab 120 MG/ML Injection',\n", " 'pneumococcal polysaccharide vaccine 23 valent',\n", " 'remdesivir 100 MG Injection',\n", " 'zoster',\n", " 'Aztreonam 2000 MG Injection',\n", " 'cefdinir', \n", " 'Cefdinir',\n", " 'doxycycline hyclate 100 MG',\n", " 'Ampicillin 100 MG/ML Injectable Solution',\n", " 'Penicillin G 375 MG/ML Injectable Solution',\n", " 'Penicillin V',\n", " 'Paclitaxel 100 MG Injection',\n", " 'Piperacillin 4000 MG / tazobactam 500 MG Injection',\n", " 'Leucovorin 100 MG Injection',\n", " 'Influenza seasonal injectable preservative free',\n", " 'Syphilis infection test',\n", " 'Skin test for tuberculosis',\n", " 'Urine culture'\n", "]\n", "\n", "\n", "df2['Injection Medications'] = df2[injection_medications_columns].sum(axis=1)\n", "category_dict['Injection Medications'] = injection_medications_columns" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "oral_medications_columns = [\n", " '12 HR Cefaclor 500 MG Extended Release Oral Tablet',\n", " '24 HR Donepezil hydrochloride 10 MG / Memantine hydrochloride 28 MG Extended Release Oral Capsule',\n", " '24 HR Metformin hydrochloride 500 MG Extended Release Oral Tablet',\n", " 'Acetaminophen 300 MG / Codeine Phosphate 15 MG Oral Tablet',\n", " 'Acetaminophen 325 MG Oral Tablet [Tylenol]',\n", " 'Alendronic acid 10 MG Oral Tablet',\n", " 'Allopurinol 100 MG Oral Tablet',\n", " 'Amlodipine 5 MG Oral Tablet',\n", " 'Amoxicillin 250 MG / Clavulanate 125 MG Oral Tablet',\n", " 'Amoxicillin 250 MG Oral Capsule',\n", " 'Aspirin 81 MG Oral Tablet',\n", " 'Astemizole 10 MG Oral Tablet',\n", " 'Atorvastatin 80 MG Oral Tablet',\n", " 'Azithromycin 250 MG Oral Tablet',\n", " 'Azithromycin 250mg',\n", " 'Cefuroxime 250 MG Oral Tablet',\n", " 'Chlorpheniramine Maleate 4 MG Oral Tablet',\n", " 'Clopidogrel 75 MG Oral Tablet',\n", " 'Colchicine 0.6 MG Oral Tablet',\n", " 'Diazepam 5 MG Oral Tablet',\n", " 'Digoxin 0.125 MG Oral Tablet',\n", " 'Donepezil hydrochloride 10 MG Oral Tablet',\n", " 'Donepezil hydrochloride 23 MG Oral Tablet',\n", " 'Doxycycline Monohydrate 100 MG Oral Tablet',\n", " 'Fexofenadine hydrochloride 60 MG Oral Tablet',\n", " 'Furosemide 40 MG Oral Tablet',\n", " 'Galantamine 4 MG Oral Tablet',\n", " 'Hydrochlorothiazide 25 MG Oral Tablet',\n", " 'Levothyroxine Sodium 0.075 MG Oral Tablet',\n", " 'Loratadine 10 MG Oral Tablet',\n", " 'Methotrexate 2.5 MG Oral Tablet',\n", " 'Milnacipran hydrochloride 100 MG Oral Tablet',\n", " 'Nitrofurantoin 5 MG/ML Oral Suspension',\n", " 'Penicillin V Potassium 500 MG Oral Tablet',\n", " 'Phenazopyridine hydrochloride 100 MG Oral Tablet',\n", " 'Sertraline 100 MG Oral Tablet',\n", " 'Simvastatin 10 MG Oral Tablet',\n", " 'Simvastatin 20 MG Oral Tablet',\n", " 'Tacrine 10 MG Oral Capsule',\n", " 'Tamoxifen 10 MG Oral Tablet',\n", " 'Terfenadine 60 MG Oral Tablet',\n", " 'Verapamil Hydrochloride 40 MG',\n", " 'Verzenio 100 MG Oral Tablet',\n", " 'Warfarin Sodium 5 MG Oral Tablet',\n", " 'palbociclib 100 MG Oral Capsule',\n", " 'predniSONE 20 MG Oral Tablet',\n", " 'ribociclib 200 MG Oral Tablet',\n", " 'neratinib 40 MG Oral Tablet',\n", " 'Hydroxychloroquine Sulfate 200 MG Oral Tablet',\n", " 'chloroquine phosphate 500 MG Oral Tablet',\n", " 'Naltrexone hydrochloride 50 MG Oral Tablet',\n", " 'lapatinib 250 MG Oral Tablet',\n", " 'cetirizine hydrochloride 10 MG Oral Tablet',\n", " 'cycloSPORINE modified 100 MG Oral Capsule',\n", " 'letrozole 2.5 MG Oral Tablet',\n", " 'exemestane 25 MG Oral Tablet',\n", " 'ferrous sulfate 325 MG Oral Tablet'\n", " \n", "]\n", "\n", "\n", "df2['Oral Medications'] = df2[oral_medications_columns].sum(axis=1)\n", "category_dict['Oral Medications'] = oral_medications_columns" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "other_medications_columns = [\n", " '0.25 ML Leuprolide Acetate 30 MG/ML Prefilled Syringe',\n", " '1 ML Epoetin Alfa 4000 UNT/ML Injection [Epogen]',\n", " '1 ML denosumab 60 MG/ML Prefilled Syringe',\n", " '10 ML Furosemide 10 MG/ML Injection',\n", " '3 ML liraglutide 6 MG/ML Pen Injector',\n", " '5 ML fulvestrant 50 MG/ML Prefilled Syringe',\n", " '12 HR Cefaclor 500 MG Extended Release Oral Tablet',\n", " '120 ACTUAT Fluticasone propionate 0.044 MG/ACTUAT Metered Dose Inhaler',\n", " '60 ACTUAT Fluticasone propionate 0.25 MG/ACTUAT / salmeterol 0.05 MG/ACTUAT Dry Powder Inhaler',\n", " 'Acetaminophen 21.7 MG/ML / Dextromethorphan Hydrobromide 1 MG/ML / doxylamine succinate 0.417 MG/ML Oral Solution',\n", " 'Chlamydia antigen test',\n", " 'Hepatitis B Surface Antigen Measurement',\n", " 'Hepatitis C antibody test',\n", " 'Human immunodeficiency virus antigen test',\n", " 'Insulin Lispro 100 UNT/ML Injectable Solution [Humalog]',\n", " 'Jolivette 28 Day Pack',\n", " 'Lymphocytes [#/volume] in Blood by Automated count',\n", " 'Measurement of Varicella-zoster virus antibody',\n", " 'Memantine hydrochloride 2 MG/ML Oral Solution',\n", " 'NDA020503 200 ACTUAT Albuterol 0.09 MG/ACTUAT Metered Dose Inhaler',\n", " 'NDA020800 0.3 ML Epinephrine 1 MG/ML Auto-Injector',\n", " 'NITROFURANTOIN MACROCRYSTALS 50 MG Oral Capsule',\n", " 'Ortho Tri-Cyclen 28 Day Pack',\n", " 'Pneumococcal conjugate PCV 13',\n", " 'Pulmozyme (Dornase Alfa)',\n", " 'SARS-COV-2 (COVID-19) vaccine mRNA spike protein LNP preservative free 100 mcg/0.5mL dose',\n", " 'SARS-COV-2 (COVID-19) vaccine mRNA spike protein LNP preservative free 30 mcg/0.3mL dose',\n", " 'SARS-COV-2 (COVID-19) vaccine vector non-replicating recombinant spike protein-Ad26 preservative free 0.5 mL',\n", " 'Seasonique 91 Day Pack',\n", " 'Td (adult) preservative free',\n", " 'Trinessa 28 Day Pack',\n", " 'Vaccination for diphtheria pertussis and tetanus',\n", " 'Vitamin B 12 5 MG/ML Injectable Solution',\n", " 'Vomiting symptom (finding)',\n", " 'Yaz 28 Day Pack',\n", " 'ado-trastuzumab emtansine 100 MG Injection',\n", " 'albuterol 5 MG/ML Inhalation Solution',\n", " 'amLODIPine 2.5 MG Oral Tablet',\n", " 'anastrozole 1 MG Oral Tablet',\n", " 'baricitinib 2 MG Oral Tablet',\n", " 'buprenorphine 2 MG / naloxone 0.5 MG Sublingual Tablet',\n", " 'carvedilol 25 MG Oral Tablet',\n", " 'sevoflurane 1000 MG/ML Inhalant Solution',\n", " 'Latex (substance)',\n", " 'desflurane 1000 MG/ML Inhalation Solution',\n", " 'Isoflurane 999 MG/ML Inhalant Solution',\n", " 'Hydrocortisone 10 MG/ML Topical Cream',\n", " 'Lenzilumab 200 MG IV',\n", " 'remifentanil 2 MG Injection',\n", " 'Carboplatin 10 MG/ML Injectable Solution',\n", " 'chloroquine phosphate 500 MG Oral Tablet',\n", " 'Naltrexone hydrochloride 50 MG Oral Tablet',\n", " 'lapatinib 250 MG Oral Tablet',\n", " 'Sodium Chloride 9 MG/ML Injectable Solution',\n", " 'insulin human isophane 70 UNT/ML / Regular Insulin Human 30 UNT/ML Injectable Suspension [Humulin]'\n", "]\n", "\n", "\n", "df2['Other Medications'] = df2[other_medications_columns].sum(axis=1)\n", "category_dict['Other Medications'] = other_medications_columns" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "therapies_and_regimes_columns = [\n", " '24hr nicotine transdermal patch',\n", " 'Assessment of health and social care needs (procedure)',\n", " 'Assessment of substance use (procedure)',\n", " 'Assessment using Alcohol Use Disorders Identification Test - Consumption (procedure)',\n", " 'Assessment using Morse Fall Scale (procedure)',\n", " 'Cognitive and behavioral therapy (regime/therapy)',\n", " 'Combined chemotherapy and radiation therapy (procedure)',\n", " 'Comprehensive interview and evaluation (procedure)',\n", " 'Construction of diverting colostomy',\n", " 'Controlled ventilation procedure and therapy initiation and management (procedure)',\n", " 'Coordination of care plan (procedure)',\n", " 'Home health aide service (regime/therapy)',\n", " 'Hospice care (regime/therapy)',\n", " 'Interstitial brachytherapy (procedure)',\n", " 'Intracavitary brachytherapy (procedure)',\n", " 'Monitoring of patient (regime/therapy)',\n", " 'Movement therapy (regime/therapy)',\n", " 'Nursing care/supplementary surveillance (regime/therapy)',\n", " 'Occupational therapy (regime/therapy)',\n", " 'Physical examination',\n", " 'Physical therapy procedure (regime/therapy)',\n", " 'Professional / ancillary services care (regime/therapy)',\n", " 'Psychosocial care (regime/therapy)',\n", " 'Pulmonary rehabilitation (regime/therapy)',\n", " 'Radiation oncology AND/OR radiotherapy (procedure)',\n", " 'Radiation therapy care (regime/therapy)',\n", " 'Referral to home health care service (procedure)',\n", " 'Referral to hypertension clinic',\n", " 'Social case work (regime/therapy)',\n", " 'Speech and language therapy regime (regime/therapy',\n", " 'Subcutaneous immunotherapy',\n", " 'Teleradiotherapy procedure (procedure)',\n", " 'Transplant of lung (procedure)',\n", " 'Transplantation of heart (procedure)',\n", " 'Weaning from mechanically assisted ventilation (procedure)',\n", " 'Microbial culture (procedure)',\n", " 'Chemotherapy (procedure)'\n", "]\n", "\n", "\n", "df2['Therapies and Regimes'] = df2[therapies_and_regimes_columns].sum(axis=1)\n", "category_dict['Therapies and Regimes'] = therapies_and_regimes_columns" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "diagnostic_procedures_columns = [\n", " 'Biopsy of breast (procedure)',\n", " 'Biopsy of colon',\n", " 'Biopsy of prostate',\n", " 'Blood typing RH typing',\n", " 'Bone density scan (procedure)',\n", " 'Chlamydia antigen test',\n", " 'Clavicle X-ray',\n", " 'Colonoscopy',\n", " 'Digital examination of rectum',\n", " 'Echocardiography (procedure)',\n", " 'Electrocardiographic procedure',\n", " 'Human epidermal growth factor receptor 2 gene detection by fluorescence in situ hybridization (procedure)',\n", " 'Human epidermal growth factor receptor 2 gene detection by immunohistochemistry (procedure)',\n", " 'Human immunodeficiency virus antigen test',\n", " 'Initial patient assessment (procedure)',\n", " 'Knee X-ray',\n", " 'Magnetic resonance imaging of breast (procedure)',\n", " 'Mammogram - symptomatic (procedure)',\n", " 'Mammography (procedure)',\n", " 'Manual pelvic examination (procedure)',\n", " 'Measurement of Varicella-zoster virus antibody',\n", " 'Measurement of respiratory function (procedure)',\n", " 'Nasal sinus endoscopy (procedure)',\n", " 'Pelvis X-ray',\n", " 'Plain chest X-ray (procedure)',\n", " 'Screening for domestic abuse (procedure)',\n", " 'Screening for drug abuse (procedure)',\n", " 'Screening for occult blood in feces (procedure)',\n", " 'Screening mammography (procedure)',\n", " 'Sentinel lymph node biopsy (procedure)',\n", " 'Spirometry (procedure)',\n", " 'Throat culture (procedure)',\n", " 'Upper arm X-ray',\n", " 'X-ray or wrist',\n", " 'Seizure Count Cerebral Cortex Electroencephalogram (EEG)',\n", " 'Allergy screening test',\n", " 'Alpha-fetoprotein test',\n", " 'Bilirubin.total [Presence] in Urine by Test strip',\n", " 'Urine screening for glucose',\n", " 'Urine screening test for diabetes',\n", " 'Urine protein test',\n", " 'Hemoglobin / Hematocrit / Platelet count',\n", " 'Assessment of anxiety (procedure)',\n", " 'Urine culture'\n", "]\n", "\n", "\n", "df2['Diagnostic Procedures'] = df2[diagnostic_procedures_columns].sum(axis=1)\n", "category_dict['Diagnostic Procedures'] = diagnostic_procedures_columns" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "surgerical_interventions_columns = [\n", " 'Admission to burn unit',\n", " 'Admission to long stay hospital',\n", " 'Admission to neurosurgical department',\n", " 'Admission to trauma surgery department',\n", " 'Admit to ICU (procedure)',\n", " 'Amputation of right foot',\n", " 'Amputation of right leg',\n", " 'Appendectomy',\n", " 'Artificial respiration (procedure)',\n", " 'Brachytherapy of breast (procedure)',\n", " 'Catheter ablation of tissue of heart',\n", " 'Coronary artery bypass grafting',\n", " 'Excision of axillary lymph node (procedure)',\n", " 'Excision of breast tissue (procedure)',\n", " 'Excision of sentinel lymph node (procedure)',\n", " 'Extraction of wisdom tooth',\n", " 'Implantation of left ventricular assist device (procedure)',\n", " 'Induced termination of pregnancy',\n", " 'Insertion of biventricular implantable cardioverter defibrillator',\n", " 'Insertion of endotracheal tube (procedure)',\n", " 'Instrumental delivery',\n", " 'Intubation',\n", " 'Laparoscopic Removal of Gall Bladder',\n", " 'Lumpectomy of breast (procedure)',\n", " 'Lung volume reduction surgery (procedure)',\n", " 'Open Removal of Gall Bladder',\n", " 'Partial resection of colon',\n", " 'Percutaneous coronary intervention',\n", " 'Percutaneous mechanical thrombectomy of portal vein using fluoroscopic guidance',\n", " 'Prostatectomy',\n", " 'Rectal polypectomy',\n", " 'Removal of endotracheal tube (procedure)',\n", " 'Removal of subcutaneous contraceptive',\n", " 'Surgical manipulation of joint of knee',\n", " 'Surgical manipulation of shoulder joint',\n", " 'Suture open wound',\n", " 'Tear of meniscus of knee',\n", " 'Transplantation of heart (procedure)'\n", "]\n", "\n", "df2['Surgical Interventions'] = df2[surgerical_interventions_columns].sum(axis=1)\n", "category_dict['Surgical Interventions'] = surgerical_interventions_columns" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "patient_care_management_columns = [\n", " 'Assessment of health and social care needs (procedure)',\n", " 'Bleeding from anus',\n", " 'Bullet wound',\n", " 'Chronic low back pain (finding)',\n", " 'Contact dermatitis',\n", " 'Cystitis',\n", " 'Diarrhea symptom (finding)',\n", " 'Escherichia coli urinary tract infection',\n", " 'Evaluation of psychiatric state of patient',\n", " 'Facial laceration',\n", " 'First degree burn',\n", " 'Heart failure education (procedure)',\n", " 'Hemodialysis (procedure)',\n", " 'Hep A adult',\n", " 'History AND physical examination (procedure)',\n", " 'History of amputation of foot (situation)',\n", " 'History of appendectomy',\n", " 'History of cardiac arrest (situation)',\n", " 'History of lower limb amputation (situation)',\n", " 'History of single seizure (situation)',\n", " 'Hospital admission short-term 24 hours',\n", " 'Information gathering (procedure)',\n", " 'Injection of tetanus antitoxin',\n", " 'Intramuscular injection',\n", " 'Intravenous blood transfusion of packed cells (procedure)',\n", " 'Intravenous injection (procedure)',\n", " 'Laceration of foot',\n", " 'Laceration of forearm',\n", " 'Laceration of hand',\n", " 'Laceration of thigh',\n", " 'Medication Reconciliation (procedure)',\n", " 'Movement therapy (regime/therapy)',\n", " 'Notifications (procedure)',\n", " 'Oxygen administration by mask (procedure)',\n", " 'Patient discharge (procedure)',\n", " 'Placing subject in prone position (procedure)',\n", " 'Postoperative procedure education (procedure)',\n", " 'Pre-discharge assessment (procedure)',\n", " 'Radiation oncology AND/OR radiotherapy (procedure)',\n", " 'Referral to home health care service (procedure)',\n", " 'Referral to hypertension clinic',\n", " 'Renal dialysis (procedure)',\n", " 'Resuscitation using intravenous fluid (procedure)',\n", " 'Review of systems (procedure)',\n", " 'Rubella screening',\n", " 'Screening mammography (procedure)',\n", " 'Subcutaneous immunotherapy',\n", " 'Teleradiotherapy procedure (procedure)',\n", " 'Transfer to stepdown unit (procedure)',\n", " 'Transfusion of plasma (procedure)',\n", " 'Weaning from mechanically assisted ventilation (procedure)',\n", " 'piperacillin 2000 MG / tazobactam 250 MG Injection',\n", " 'vancomycin 1000 MG Injection',\n", " 'Recurrent urinary tract infection',\n", " 'Acquired coagulation disorder (disorder)',\n", " 'Primary malignant neoplasm of colon',\n", " 'Pyelonephritis',\n", " 'Chill (finding)',\n", " 'Acute Cholecystitis',\n", " 'Cholelithiasis',\n", " 'Appendicitis',\n", " 'Metastasis from malignant tumor of prostate (disorder)',\n", " 'Overlapping malignant neoplasm of colon',\n", " 'Polyp of colon',\n", " 'Neoplasm of prostate',\n", " 'Carcinoma in situ of prostate (disorder)',\n", " 'Recurrent rectal polyp',\n", " 'Discharge from skilled nursing facility (procedure)',\n", " 'Certification procedure (procedure)',\n", " 'Development of individualized plan of care (procedure)'\n", "]\n", "\n", "df2['Patient Care Management'] = df2[patient_care_management_columns].sum(axis=1)\n", "category_dict['Patient Care Management'] = patient_care_management_columns" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "categories = ['Respiratory Disorders', 'Heart and Cardiovascular Diseases', 'Metabolic and Endocrine Disorders', 'Neurological Disorders', 'Orthopedic Injuries', 'Mental Health', 'Reproductive and Pregnancy', 'Pain Relievers and Analesics', 'Cardiovascular and Blood Pressure', 'Injection Medications', 'Oral Medications', 'Other Medications', 'Therapies and Regimes', 'Diagnostic Procedures', 'Surgical Interventions', 'Patient Care Management']" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Column: Screening for domestic abuse (procedure)\n", "Data Type: object\n", "Column: Osteoporosis (disorder)\n", "Data Type: object\n", "Column: Asthma screening\n", "Data Type: object\n", "Column: Influenza virus B RNA [Presence] in Respiratory specimen by NAA with probe detection\n", "Data Type: object\n", "Column: Appearance of Urine\n", "Data Type: object\n", "Column: 1 ML Enoxaparin sodium 150 MG/ML Prefilled Syringe\n", "Data Type: object\n", "Column: Brief general examination (procedure)\n", "Data Type: object\n", "Column: letrozole 2.5 MG Oral Tablet\n", "Data Type: object\n", "Column: SARS-CoV-2 RNA Pnl Resp NAA+probe\n", "Data Type: object\n", "Column: Limited social contact (finding)\n", "Data Type: object\n", "Column: Primary fibromyalgia syndrome\n", "Data Type: object\n", "Column: Camila 28 Day Pack\n", "Data Type: object\n", "Column: Body temperature\n", "Data Type: object\n", "Column: Intubation\n", "Data Type: object\n", "Column: ribociclib 200 MG Oral Tablet\n", "Data Type: object\n", "Column: Sodium Chloride 9 MG/ML Injectable Solution\n", "Data Type: object\n", "Column: Acute bacterial sinusitis (disorder)\n", "Data Type: object\n", "Column: Spontaneous breech delivery\n", "Data Type: object\n", "Column: Auscultation of the fetal heart\n", "Data Type: object\n", "Column: Total Bilirubin (Elevated)\n", "Data Type: float64\n", "Column: 0.3 ML Enoxaparin sodium 100 MG/ML Prefilled Syringe\n", "Data Type: object\n", "Column: Sore throat symptom (finding)\n", "Data Type: object\n", 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"Column: Streptococcus pneumoniae group B antigen test\n", "Data Type: object\n", "Column: Levothyroxine Sodium 0.075 MG Oral Tablet\n", "Data Type: object\n", "Column: Protein [Mass/volume] in Urine by Test strip\n", "Data Type: object\n", "Column: amLODIPine 2.5 MG Oral Tablet\n", "Data Type: object\n", "Column: Blood typing RH typing\n", "Data Type: object\n", "Column: White Blood Cell (Elevated)\n", "Data Type: float64\n", "Column: desflurane 1000 MG/ML Inhalation Solution\n", "Data Type: object\n", "Column: Tubal pregnancy\n", "Data Type: object\n", "Column: 3 ML liraglutide 6 MG/ML Pen Injector\n", "Data Type: object\n", "Column: Diarrhea symptom (finding)\n", "Data Type: object\n", "Column: predniSONE 20 MG Oral Tablet\n", "Data Type: object\n", "Column: Hypertension\n", "Data Type: object\n", "Column: Acute viral pharyngitis (disorder)\n", "Data Type: object\n", "Column: Tree pollen (substance)\n", "Data Type: object\n", "Column: Wheat IgE Ab in Serum\n", "Data Type: object\n", 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object\n", "Column: Iron binding capacity [Mass/volume] in Serum or Plasma\n", "Data Type: object\n", "Column: Red Blood Cell\n", "Data Type: float64\n", "Column: Rheumatoid arthritis\n", "Data Type: object\n", "Column: Care regimes assessment (procedure)\n", "Data Type: object\n", "Column: buprenorphine 2 MG / naloxone 0.5 MG Sublingual Tablet\n", "Data Type: object\n", "Column: vancomycin 1000 MG Injection\n", "Data Type: object\n", "Column: Sweat Test\n", "Data Type: float64\n", "Column: Proteinuria due to type 2 diabetes mellitus (disorder)\n", "Data Type: object\n", "Column: Acetaminophen 500 MG Oral Tablet\n", "Data Type: object\n", "Column: Hemoglobin [Mass/volume] in Blood\n", "Data Type: object\n", "Column: Fracture of forearm\n", "Data Type: object\n", "Column: Extraction of wisdom tooth\n", "Data Type: object\n", "Column: 3 ML Amiodarone hydrocholoride 50 MG/ML Prefilled Syringe\n", "Data Type: object\n", "Column: Episiotomy\n", "Data Type: object\n", "Column: 5 ML fulvestrant 50 MG/ML Prefilled Syringe\n", "Data Type: object\n", "Column: 10 ML Doxorubicin Hydrochloride 2 MG/ML Injection\n", "Data Type: object\n", "Column: Insertion of biventricular implantable cardioverter defibrillator\n", "Data Type: object\n", "Column: Chronic obstructive bronchitis (disorder)\n", "Data Type: object\n", "Column: Evaluation of psychiatric state of patient\n", "Data Type: object\n", "Column: Skin test for tuberculosis\n", "Data Type: object\n", "Column: Colonoscopy\n", "Data Type: object\n", "Column: Systolic Blood Pressure\n", "Data Type: object\n", "Column: Abuse Status [OMAHA]\n", "Data Type: object\n", "Column: Myocardial Infarction\n", "Data Type: object\n", "Column: HER2 [Presence] in Breast cancer specimen by Immune stain\n", "Data Type: object\n", "Column: Spirometry (procedure)\n", "Data Type: object\n", "Column: Instrumental delivery\n", "Data Type: object\n", "Column: remifentanil 2 MG Injection\n", "Data Type: object\n", "Column: Hemoglobin 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object\n", "Column: HER2 [Presence] in Breast cancer specimen by FISH\n", "Data Type: object\n", "Column: Acute pulmonary embolism (disorder)\n", "Data Type: object\n", "Column: Cesarean section\n", "Data Type: object\n", "Column: Mental health screening (procedure)\n", "Data Type: object\n", "Column: Miscarriage in first trimester\n", "Data Type: object\n", "Column: remdesivir 100 MG Injection\n", "Data Type: float64\n", "Column: anastrozole 1 MG Oral Tablet\n", "Data Type: object\n", "Column: Pelvis X-ray\n", "Data Type: object\n", "Column: Naproxen 500 MG Oral Tablet\n", "Data Type: object\n", "Column: Chronic paralysis due to lesion of spinal cord\n", "Data Type: object\n", "Column: 1 ML DOCEtaxel 20 MG/ML Injection\n", "Data Type: object\n", "Column: Transplant of lung (procedure)\n", "Data Type: object\n", "Column: Digoxin 0.125 MG Oral Tablet\n", "Data Type: object\n", "Column: Ultrasound scan for fetal viability\n", "Data Type: object\n", "Column: Sepsis caused by virus 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Catheter ablation of tissue of heart\n", "Data Type: object\n", "Column: Donepezil hydrochloride 23 MG Oral Tablet\n", "Data Type: object\n", "Column: Speech and language therapy regime (regime/therapy\n", "Data Type: object\n", "Column: cetirizine hydrochloride 10 MG Oral Tablet\n", "Data Type: object\n", "Column: Radiation oncology AND/OR radiotherapy (procedure)\n", "Data Type: object\n", "Column: Lupus erythematosus\n", "Data Type: float64\n", "Column: Bicarbonate [Moles/volume] in Arterial blood\n", "Data Type: float64\n", "Column: Penicillin V Potassium 500 MG Oral Tablet\n", "Data Type: object\n", "Column: NDA020503 200 ACTUAT Albuterol 0.09 MG/ACTUAT Metered Dose Inhaler\n", "Data Type: object\n", "Column: Manual pelvic examination (procedure)\n", "Data Type: object\n", "Column: SARS-COV-2 (COVID-19) vaccine mRNA spike protein LNP preservative free 100 mcg/0.5mL dose\n", "Data Type: object\n", "Column: Fracture of rib\n", "Data Type: object\n", "Column: Aspirin\n", "Data Type: object\n", "Column: Bilateral tubal ligation\n", "Data Type: object\n", "Column: Leronlimab 700 MG Injection\n", "Data Type: float64\n", "Column: Urine screening test for diabetes\n", "Data Type: object\n", "Column: losartan potassium 50 MG Oral Tablet\n", "Data Type: object\n", "Column: At risk for suicide (finding)\n", "Data Type: object\n", "Column: Tear of meniscus of knee\n", "Data Type: object\n", "Column: Admission to burn unit\n", "Data Type: object\n", "Column: Chronic pain\n", "Data Type: object\n", "Column: Pre-discharge assessment (procedure)\n", "Data Type: object\n", "Column: Cystic Fibrosis\n", "Data Type: float64\n", "Column: Vomiting symptom (finding)\n", "Data Type: object\n", "Column: Chronic kidney disease stage 3 (disorder)\n", "Data Type: object\n", "Column: Bacterial infectious disease (disorder)\n", "Data Type: object\n", "Column: Peanut IgE Ab in Serum\n", "Data Type: object\n", "Column: Fexofenadine hydrochloride 60 MG Oral Tablet\n", "Data Type: object\n", "Column: insulin human isophane 70 UNT/ML / Regular Insulin Human 30 UNT/ML Injectable Suspension [Humulin]\n", "Data Type: object\n", "Column: 60 ACTUAT Fluticasone propionate 0.25 MG/ACTUAT / salmeterol 0.05 MG/ACTUAT Dry Powder Inhaler\n", "Data Type: object\n", "Column: Mental health Outpatient Note\n", "Data Type: float64\n", "Column: Transfusion of plasma (procedure)\n", "Data Type: object\n", "Column: Pulmonary emphysema (disorder)\n", "Data Type: object\n", "Column: Severe anxiety (panic) (finding\n", "Data Type: object\n", "Column: SARS-COV-2 (COVID-19) vaccine vector non-replicating recombinant spike protein-Ad26 preservative free 0.5 mL\n", "Data Type: object\n", "Column: Lenzilumab 200 MG IV\n", "Data Type: float64\n", "Column: Heart rate\n", "Data Type: object\n", "Column: Hemoglobin.gastrointestinal [Presence] in Stool by Immunologic method\n", "Data Type: object\n", "Column: Allergy screening test\n", "Data Type: object\n", "Column: 1 ML Epoetin Alfa 4000 UNT/ML Injection [Epogen]\n", "Data Type: object\n", "Column: exemestane 25 MG Oral Tablet\n", "Data Type: object\n", "Column: 10 ML Furosemide 10 MG/ML Injection\n", "Data Type: object\n", "Column: Social isolation (finding)\n", "Data Type: object\n", "Column: History of lower limb amputation (situation)\n", "Data Type: object\n", "Column: Microalbuminuria due to type 2 diabetes mellitus (disorder)\n", "Data Type: object\n", "Column: Coronary artery bypass grafting\n", "Data Type: object\n", "Column: Bone immobilization\n", "Data Type: object\n", "Column: Respiratory syncytial virus RNA [Presence] in Respiratory specimen by NAA with probe detection\n", "Data Type: object\n", "Column: Erythrocyte distribution width [Entitic volume] by Automated count\n", "Data Type: object\n", "Column: 5 ML hyaluronidase-oysk 2000 UNT/ML / trastuzumab 120 MG/ML Injection\n", "Data Type: object\n", "Column: Refugee (person)\n", "Data Type: object\n", "Column: Stress (finding)\n", "Data Type: object\n", "Column: Referral to hypertension clinic\n", "Data Type: object\n", "Column: Oxygen Therapy\n", "Data Type: object\n", "Column: Non-low risk pregnancy\n", "Data Type: float64\n", "Column: Biopsy of colon\n", "Data Type: object\n", "Column: Muscle pain (finding)\n", "Data Type: object\n", "Column: Victim of intimate partner abuse (finding)\n", "Data Type: object\n", "Column: Admission to long stay hospital\n", "Data Type: object\n", "Column: ado-trastuzumab emtansine 100 MG Injection\n", "Data Type: float64\n", "Column: Response to cancer treatment\n", "Data Type: object\n", "Column: Information gathering (procedure)\n", "Data Type: object\n", "Column: Fibromyalgia (disorder)\n", "Data Type: object\n", "Column: Rectal polypectomy\n", "Data Type: object\n", "Column: INR in Platelet poor plasma by Coagulation assay\n", "Data Type: float64\n", "Column: Walnut IgE Ab in Serum\n", "Data Type: object\n", "Column: Polyp size greatest dimension by CAP cancer protocols\n", "Data Type: object\n", "Column: Admission to orthopedic department\n", "Data Type: object\n", "Column: Depression screening using Patient Health Questionnaire Two-Item score (procedure)\n", "Data Type: object\n", "Column: Protein [Presence] in Urine by Test strip\n", "Data Type: object\n", "Column: Clarity of Urine\n", "Data Type: object\n", "Column: Amputation of right foot\n", "Data Type: object\n", "Column: Injury of heart (disorder)\n", "Data Type: object\n", "Column: Prediabetes\n", "Data Type: object\n", "Column: NuvaRing 0.12/0.015 MG per 24HR 21 Day Vaginal Ring\n", "Data Type: object\n", "Column: Pancreatin 600 MG Oral Tablet\n", "Data Type: float64\n", "Column: Infection caused by Staphylococcus aureus\n", "Data Type: float64\n", "Column: Sentinel lymph node biopsy (procedure)\n", "Data Type: object\n", "Column: Memantine hydrochloride 2 MG/ML Oral Solution\n", "Data Type: object\n", "Column: Yaz 28 Day Pack\n", "Data Type: object\n", "Column: Prothrombin time (PT)\n", "Data Type: float64\n", "Column: Acetaminophen 325 MG Oral Tablet [Tylenol]\n", "Data Type: object\n", "Column: Gonorrhea infection test\n", "Data Type: object\n", "Column: Oxygen saturation in Arterial blood\n", "Data Type: object\n", "Column: Digital examination of rectum\n", "Data Type: object\n", "Column: Weaning from mechanically assisted ventilation (procedure)\n", "Data Type: object\n", "Column: Sertraline 100 MG Oral Tablet\n", "Data Type: object\n", "Column: Fracture subluxation of wrist\n", "Data Type: object\n", "Column: pneumococcal polysaccharide vaccine 23 valent\n", "Data Type: object\n", "Column: Cat dander IgE Ab in Serum\n", "Data Type: object\n", "Column: DXA [T-score] Bone density\n", "Data Type: object\n", "Column: Diabetic retinopathy associated with type II diabetes mellitus (disorder)\n", "Data Type: object\n", "Column: Premature birth of newborn\n", "Data Type: object\n", "Column: Honey bee IgE Ab in Serum\n", "Data Type: object\n", "Column: Cefdinir\n", "Data Type: object\n", "Column: Bullet wound\n", "Data Type: object\n", "Column: 150 ML vancomycin 5 MG/ML Injection\n", "Data Type: object\n", "Column: Smokes tobacco daily\n", "Data Type: object\n", "Column: Carbon dioxide [Partial pressure] in Arterial blood\n", "Data Type: float64\n", "Column: Mold (organism)\n", "Data Type: object\n", "Column: Vasectomy\n", "Data Type: object\n", "Column: Influenza virus B Ag [Presence] in Nasopharynx by Rapid immunoassay\n", "Data Type: object\n", "Column: Acute respiratory distress syndrome (disorder)\n", "Data Type: object\n", "Column: Creatine kinase [Enzymatic activity/volume] in Serum or Plasma\n", "Data Type: float64\n", "Column: Implantation of left ventricular assist device (procedure)\n", "Data Type: object\n", "Column: 1 ML Morphine Sulfate 5 MG/ML Injection\n", "Data Type: object\n", "Column: Leukocyte esterase [Presence] in Urine by Test strip\n", "Data Type: object\n", "Column: Oral Glucose Tolerance Test\n", "Data Type: float64\n", "Column: lapatinib 250 MG Oral Tablet\n", "Data Type: float64\n", "Column: Unhealthy alcohol drinking behavior (finding)\n", "Data Type: object\n", "Column: Biopsy of prostate\n", "Data Type: object\n", "Column: Injury of kidney (disorder)\n", "Data Type: object\n", "Column: Monocytes [#/volume] in Blood by Automated count\n", "Data Type: float64\n", "Column: Ortho Tri-Cyclen 28 Day Pack\n", "Data Type: object\n", "Column: Vitamin B 12 5 MG/ML Injectable Solution\n", "Data Type: object\n", "Column: Chloride [Moles/volume] in Serum or Plasma\n", "Data Type: object\n", "Column: lisinopril 10 MG Oral Tablet\n", "Data Type: object\n", "Column: Nasal sinus endoscopy (procedure)\n", "Data Type: object\n", "Column: NITROFURANTOIN MACROCRYSTALS 50 MG Oral Capsule\n", "Data Type: object\n", "Column: History of myocardial infarction (situation)\n", "Data Type: object\n", "Column: 10 ML Fluorouracil 50 MG/ML Injection\n", "Data Type: object\n", "Column: Total replacement of hip\n", "Data Type: object\n", "Column: 100 ML Propofol 10 MG/ML Injection\n", "Data Type: object\n", "Column: Chloride\n", "Data Type: object\n", "Column: Tacrine 10 MG Oral Capsule\n", "Data Type: object\n", "Column: Glucose [Presence] in Urine by Test strip\n", "Data Type: object\n", "Column: Pyelonephritis\n", "Data Type: object\n", "Column: Incision of trachea (procedure)\n", "Data Type: float64\n", "Column: Bee venom (substance)\n", "Data Type: float64\n", "Column: sacubitril 97 MG / valsartan 103 MG Oral Tablet\n", "Data Type: object\n", "Column: Professional / ancillary services care (regime/therapy)\n", "Data Type: object\n", "Column: Impacted molars\n", "Data Type: object\n", "Column: Mammogram - symptomatic (procedure)\n", "Data Type: object\n", "Column: Rupture of appendix\n", "Data Type: object\n", "Column: Penicillin V\n", "Data Type: object\n", "Column: Coronary Heart Disease\n", "Data Type: object\n", "Column: Subcutaneous immunotherapy\n", "Data Type: object\n", "Column: Stage group.clinical Cancer\n", "Data Type: object\n", "Column: Septic shock (disorder)\n", "Data Type: object\n", "Column: Antepartum eclampsia\n", "Data Type: object\n", "Column: Housing status\n", "Data Type: object\n", "Column: Comprehensive interview and evaluation (procedure)\n", "Data Type: object\n", "Column: Resuscitation using intravenous fluid (procedure)\n", "Data Type: object\n", "Column: Induced termination of pregnancy\n", "Data Type: object\n", "Column: Assessment using New York Heart Association Classification (procedure)\n", "Data Type: object\n", "Column: Coordination of care plan (procedure)\n", "Data Type: object\n", "Column: White oak IgE Ab in Serum\n", "Data Type: object\n", "Column: Phenazopyridine hydrochloride 100 MG Oral Tablet\n", "Data Type: object\n", "Column: Basophils [#/volume] in Blood by Automated count\n", "Data Type: float64\n", "Column: Ibuprofen\n", "Data Type: float64\n", "Column: Assessment using Alcohol Use Disorders Identification Test - Consumption (procedure)\n", "Data Type: object\n", "Column: Social migrant (finding)\n", "Data Type: float64\n", "Column: Has a criminal record (finding)\n", "Data Type: object\n", "Column: Seizure Count Cerebral Cortex Electroencephalogram (EEG)\n", "Data Type: object\n", "Column: Oxygen administration by mask (procedure)\n", "Data Type: object\n", "Column: Social case work (regime/therapy)\n", "Data Type: object\n", "Column: Screening mammography (procedure)\n", "Data Type: object\n", "Column: Assessment of anxiety (procedure)\n", "Data Type: object\n", "Column: Contact dermatitis\n", "Data Type: object\n", "Column: FEV1/FVC\n", "Data Type: object\n", "Column: Body mass index 40+ - severely obese (finding)\n", "Data Type: object\n", "Column: Removal of subcutaneous contraceptive\n", "Data Type: object\n", "Column: Hydrocortisone 10 MG/ML Topical Cream\n", "Data Type: object\n", "Column: Assessment using Morse Fall Scale (procedure)\n", "Data Type: object\n", "Column: Parainfluenza virus 2 RNA [Presence] in Respiratory specimen by NAA with probe detection\n", "Data Type: object\n", "Column: Anemia (disorder)\n", "Data Type: object\n", "Column: Urine culture\n", "Data Type: object\n", "Column: Surgical manipulation of shoulder joint\n", "Data Type: object\n", "Column: Transplantation of heart (procedure)\n", "Data Type: object\n", "Column: Eosinophils [#/volume] in Blood by Automated count\n", "Data Type: float64\n", "Column: Heart failure (disorder)\n", "Data Type: object\n", "Column: Intravenous infusion (procedure)\n", "Data Type: float64\n", "Column: Latex (substance)\n", "Data Type: float64\n", "Column: Acute bronchitis (disorder)\n", "Data Type: object\n", "Column: 5 ML SUFentanil 0.05 MG/ML Injection\n", "Data Type: object\n", "Column: Lung Transplant\n", "Data Type: float64\n", "Column: Ampicillin 100 MG/ML Injectable Solution\n", "Data Type: object\n", "Column: Human metapneumovirus RNA [Presence] in Respiratory specimen by NAA with probe detection\n", "Data Type: object\n", "Column: Injection of tetanus antitoxin\n", "Data Type: object\n", "Column: Td (adult) preservative free\n", "Data Type: object\n", "Column: Sulfamethoxazole / Trimethoprim\n", "Data Type: object\n", "Column: Heart failure education (procedure)\n", "Data Type: object\n", "Column: NDA020800 0.3 ML Epinephrine 1 MG/ML Auto-Injector\n", "Data Type: object\n", "Column: Total Cholesterol\n", "Data Type: object\n", "Column: Initial patient assessment (procedure)\n", "Data Type: object\n", "Column: Blighted ovum\n", "Data Type: object\n", "Column: cycloSPORINE modified 100 MG Oral Capsule\n", "Data Type: object\n", "Column: Adenovirus A+B+C+D+E DNA [Presence] in Respiratory specimen by NAA with probe detection\n", "Data Type: object\n", "Column: SARS-COV-2 (COVID-19) vaccine mRNA spike protein LNP preservative free 30 mcg/0.3mL dose\n", "Data Type: object\n", "Column: Treatment status Cancer\n", "Data Type: object\n", "Column: Hospice care (regime/therapy)\n", "Data Type: object\n", "Column: Laceration of foot\n", "Data Type: object\n", "Column: Acetaminophen 325 MG / Oxycodone Hydrochloride 10 MG Oral Tablet [Percocet]\n", "Data Type: object\n", "Column: Lisinopril\n", "Data Type: object\n", "Column: Iron saturation [Mass Fraction] in Serum or Plasma\n", "Data Type: object\n", "Column: Osteoarthritis of hip\n", "Data Type: object\n", "Column: Urine screening for glucose\n", "Data Type: object\n", "Column: Jolivette 28 Day Pack\n", "Data Type: object\n", "Column: Malignant neoplasm of breast (disorder)\n", "Data Type: object\n", "Column: Psychosocial care (regime/therapy)\n", "Data Type: object\n", "Column: Reports of violence in the environment (finding)\n", "Data Type: object\n", "Column: Hyperlipidemia\n", "Data Type: object\n", "Column: Plain chest X-ray (procedure)\n", "Data Type: object\n", "Column: Human epidermal growth factor receptor 2 gene detection by fluorescence in situ hybridization (procedure)\n", "Data Type: object\n", "Column: Percutaneous mechanical thrombectomy of portal vein using fluoroscopic guidance\n", "Data Type: object\n", "Column: Preeclampsia\n", "Data Type: object\n", "Column: Diazepam 5 MG/ML Injectable Solution\n", "Data Type: float64\n", "Column: History of appendectomy\n", "Data Type: object\n", "Column: Loratadine 10 MG Oral Tablet\n", "Data Type: object\n", "Column: Cystitis\n", "Data Type: object\n", "Column: Common Ragweed IgE Ab in Serum\n", "Data Type: object\n", "Column: Loss of taste (finding)\n", "Data Type: object\n", "Column: Low Density Lipoprotein Cholesterol\n", "Data Type: object\n", "Column: 24 HR Donepezil hydrochloride 10 MG / Memantine hydrochloride 28 MG Extended Release Oral Capsule\n", "Data Type: object\n", "Column: baricitinib 2 MG Oral Tablet\n", "Data Type: float64\n", "Column: Bleeding from anus\n", "Data Type: object\n", "Column: Occupational therapy (regime/therapy)\n", "Data Type: object\n", "Column: Urine protein test\n", "Data Type: object\n", "Column: ferrous sulfate 325 MG Oral Tablet\n", "Data Type: object\n", "Column: Excision of breast tissue (procedure)\n", "Data Type: object\n", "Column: Acetaminophen/Hydrocodone\n", "Data Type: object\n", "Column: Excision of fallopian tube and surgical removal of ectopic pregnancy\n", "Data Type: object\n", "Column: Bilirubin.total [Mass/volume] in Urine by Test strip\n", "Data Type: object\n", "Column: Removal of intrauterine device\n", "Data Type: object\n", "Column: Surgical manipulation of joint of knee\n", "Data Type: object\n", "Column: albuterol 5 MG/ML Inhalation Solution\n", "Data Type: object\n", "Column: Admission to trauma surgery department\n", "Data Type: object\n", "Column: Furosemide 40 MG Oral Tablet\n", "Data Type: object\n", "Column: Leucovorin 100 MG Injection\n", "Data Type: object\n", "Column: neratinib 40 MG Oral Tablet\n", "Data Type: object\n", "Column: Physical therapy procedure (regime/therapy)\n", "Data Type: object\n", "Column: Medical induction of labor\n", "Data Type: object\n", "Column: Shrimp IgE Ab in Serum\n", "Data Type: object\n", "Column: Human immunodeficiency virus antigen test\n", "Data Type: object\n", "Column: Concussion with no loss of consciousness\n", "Data Type: object\n", "Column: Diabetes\n", "Data Type: object\n", "Column: Recurrent rectal polyp\n", "Data Type: object\n", "Column: Vancomycin 50 MG/ML Injectable Solution\n", "Data Type: float64\n", "Column: Ketones [Mass/volume] in Urine by Test strip\n", "Data Type: object\n", "Column: Amoxicillin 250 MG Oral Capsule\n", "Data Type: object\n", "Column: Intracavitary brachytherapy (procedure)\n", "Data Type: object\n", "Column: Face mask (physical object)\n", "Data Type: object\n", "Column: zoster\n", "Data Type: object\n", "Column: Nitrofurantoin 5 MG/ML Oral Suspension\n", "Data Type: object\n", "Column: Acute Cholecystitis\n", "Data Type: object\n", "Column: Polyp of colon\n", "Data Type: object\n", "Column: Neutrophils [#/volume] in Blood by Automated count\n", "Data Type: float64\n", "Column: Metabolic syndrome X (disorder)\n", "Data Type: object\n", "Column: Globulin [Mass/volume] in Serum by calculation\n", "Data Type: object\n", "Column: History AND physical examination (procedure)\n", "Data Type: object\n", "Column: 10 ML Pamidronate Disodium 3 MG/ML Injection\n", "Data Type: object\n", "Column: Alcoholism\n", "Data Type: object\n", "Column: Part-time employment (finding)\n", "Data Type: object\n", "Column: 0.25 ML Leuprolide Acetate 30 MG/ML Prefilled Syringe\n", "Data Type: object\n", "Column: HIV status\n", "Data Type: object\n", "Column: duloxetine 20 MG Delayed Release Oral Capsule\n", "Data Type: object\n", "Column: Soybean IgE Ab in Serum\n", "Data Type: object\n", "Column: Wheezing (finding)\n", "Data Type: object\n", "Column: Chronic sinusitis (disorder)\n", "Data Type: object\n", "Column: Verapamil Hydrochloride 40 MG\n", "Data Type: object\n", "Column: Measurement of Varicella-zoster virus antibody\n", "Data Type: object\n", "Column: Functional capacity NYHA\n", "Data Type: object\n", "Column: Calcium [Mass/volume] in Serum or Plasma\n", "Data Type: object\n", "Column: Construction of diverting colostomy\n", "Data Type: object\n", "Column: Discharge from skilled nursing facility (procedure)\n", "Data Type: object\n", "Column: Peripheral blood smear interpretation\n", "Data Type: object\n", "Column: Pregnancy termination care\n", "Data Type: object\n", "Column: Attempted suicide - suffocation\n", "Data Type: float64\n", "Column: 168 HR Ethinyl Estradiol 0.00146 MG/HR / norelgestromin 0.00625 MG/HR Transdermal System\n", "Data Type: object\n", "Column: Basophils/100 leukocytes in Blood by Automated count\n", "Data Type: float64\n", "Column: MCV\n", "Data Type: float64\n", "Column: Azithromycin 250mg\n", "Data Type: object\n", "Column: Syphilis infection test\n", "Data Type: object\n", "Column: Antenatal RhD antibody screening\n", "Data Type: object\n", "Column: state\n", "Data Type: object\n", "Column: Streptococcal sore throat (disorder)\n", "Data Type: object\n", "Column: Second degree burn\n", "Data Type: object\n", "Column: Lumpectomy of breast (procedure)\n", "Data Type: object\n", "Column: 120 ACTUAT Fluticasone propionate 0.044 MG/ACTUAT Metered Dose Inhaler\n", "Data Type: object\n", "Column: Measurement of respiratory function (procedure)\n", "Data Type: object\n", "Column: Brain damage - traumatic\n", "Data Type: object\n", "Column: X-ray or wrist\n", "Data Type: object\n", "Column: Insertion of intrauterine contraceptive device\n", "Data Type: object\n", "Column: Cladosporium herbarum IgE Ab in Serum\n", "Data Type: object\n", "Column: lisinopril 20 MG Oral Tablet\n", "Data Type: object\n", "Column: Thyroxine (T4) free [Mass/volume] in Serum or Plasma\n", "Data Type: object\n", "Column: Otitis media\n", "Data Type: object\n", "Column: Oxygen/Inspired gas setting [Volume Fraction] Ventilator\n", "Data Type: float64\n", "Column: Chronic congestive heart failure (disorder)\n", "Data Type: object\n", "Column: losartan potassium 25 MG Oral Tablet\n", "Data Type: object\n", "Column: MCHC [Mass/volume] by Automated count\n", "Data Type: object\n", "Column: Full-time employment (finding)\n", "Data Type: object\n", "Column: Echocardiography (procedure)\n", "Data Type: object\n", "Column: age\n", "Data Type: object\n", "Column: Suture open wound\n", "Data Type: object\n", "Column: Radiation therapy care (regime/therapy)\n", "Data Type: object\n", "Column: Laceration of thigh\n", "Data Type: object\n", "Column: Fracture of ankle\n", "Data Type: object\n", "Column: Glucose\n", "Data Type: object\n", "Column: Allopurinol 100 MG Oral Tablet\n", "Data Type: object\n", "Column: Idiopathic atrophic hypothyroidism\n", "Data Type: object\n", "Column: Ankle X-ray\n", "Data Type: object\n", "Column: Fever (finding)\n", "Data Type: object\n", "Column: Aztreonam 2000 MG Injection\n", "Data Type: object\n", "Column: Diabetic renal disease (disorder)\n", "Data Type: object\n", "Column: Platelet mean volume [Entitic volume] in Blood by Automated count\n", "Data Type: object\n", "Column: Drug overdose\n", "Data Type: object\n", "Column: Depression screening using Patient Health Questionnaire Nine Item score (procedure)\n", "Data Type: object\n", "Column: Influenza virus A RNA [Presence] in Respiratory specimen by NAA with probe detection\n", "Data Type: object\n", "Column: NT-proBNP\n", "Data Type: object\n", "Column: First degree burn\n", "Data Type: object\n", "Column: Amputation of right leg\n", "Data Type: float64\n", "Column: Alanine aminotransferase [Enzymatic activity/volume] in Serum or Plasma\n", "Data Type: object\n", "Column: Standard pregnancy test\n", "Data Type: object\n", "Column: Vaccination for diphtheria pertussis and tetanus\n", "Data Type: object\n", "Column: 0.4 ML Enoxaparin sodium 100 MG/ML Prefilled Syringe\n", "Data Type: object\n", "Column: Glucose [Mass/volume] in Urine by Test strip\n", "Data Type: object\n", "Column: Interstitial brachytherapy (procedure)\n", "Data Type: object\n", "Column: label\n", "Data Type: int64\n", "Column: Closed fracture of hip\n", "Data Type: object\n", "Column: Triglycerides\n", "Data Type: object\n", "Column: Penicillin G 375 MG/ML Injectable Solution\n", "Data Type: object\n", "Column: Assessment of substance use (procedure)\n", "Data Type: object\n", "Column: Appendectomy\n", "Data Type: object\n", "Column: Joint pain (finding)\n", "Data Type: object\n", "Column: Chlamydia antigen test\n", "Data Type: object\n", "Column: Clopidogrel 75 MG Oral Tablet\n", "Data Type: object\n", "Column: Albumin\n", "Data Type: object\n", "Column: Liletta 52 MG Intrauterine System\n", "Data Type: object\n", "Column: Iron [Mass/volume] in Serum or Plasma\n", "Data Type: object\n", "Column: Intramuscular injection\n", "Data Type: object\n", "Column: Galantamine 4 MG Oral Tablet\n", "Data Type: object\n", "Column: Intravenous blood transfusion of packed cells (procedure)\n", "Data Type: object\n", "Column: Pulmozyme (Dornase Alfa)\n", "Data Type: float64\n", "Column: Laceration of hand\n", "Data Type: object\n", "Column: Potassium\n", "Data Type: object\n", "Column: Carbamazepine[Tegretol]\n", "Data Type: object\n", "Column: Neoplasm of prostate\n", "Data Type: object\n", "Column: Depression screening (procedure)\n", "Data Type: object\n", "Column: Bone density scan (procedure)\n", "Data Type: object\n", "Column: Urea Nitrogen\n", "Data Type: object\n", "Column: Hydrochlorothiazide 25 MG Oral Tablet\n", "Data Type: object\n", "Column: Atrial Fibrillation\n", "Data Type: object\n", "Column: Not in labor force (finding)\n", "Data Type: object\n", "Column: Insertion of endotracheal tube (procedure)\n", "Data Type: object\n", "Column: Homeless (finding)\n", "Data Type: object\n", "Column: Asthma\n", "Data Type: object\n", "Column: Alendronic acid 10 MG Oral Tablet\n", "Data Type: object\n", "Column: Postoperative procedure education (procedure)\n", "Data Type: object\n", "Column: Screening for drug abuse (procedure)\n", "Data Type: object\n", "Column: Cefuroxime 250 MG Oral Tablet\n", "Data Type: object\n", "Column: 0.67 ML anakinra 149 MG/ML Prefilled Syringe\n", "Data Type: float64\n", "Column: Respiratory rate\n", "Data Type: object\n", "Column: 1 ML heparin sodium porcine 5000 UNT/ML Injection\n", "Data Type: object\n", "Column: Intravenous antibiotic therapy\n", "Data Type: float64\n", "Column: Objective assessment of cardiovascular disease NYHA\n", "Data Type: object\n", "Column: Ferritin [Mass/volume] in Serum or Plasma\n", "Data Type: object\n", "Column: gender\n", "Data Type: object\n", "Column: Teleradiotherapy procedure (procedure)\n", "Data Type: object\n", "Column: Urea nitrogen [Mass/volume] in Serum or Plasma\n", "Data Type: object\n", "Column: Grass pollen (substance)\n", "Data Type: float64\n", "Column: House dust mite (organism)\n", "Data Type: object\n", "Column: Neuropathy due to type 2 diabetes mellitus (disorder)\n", "Data Type: object\n", "Column: Etonogestrel 68 MG Drug Implant\n", "Data Type: object\n", "Column: 12 HR Cefaclor 500 MG Extended Release Oral Tablet\n", "Data Type: object\n", "Column: Carcinoma in situ of prostate (disorder)\n", "Data Type: object\n", "Column: Simvastatin 10 MG Oral Tablet\n", "Data Type: object\n", "Column: cefdinir\n", "Data Type: object\n", "Column: scc\n", "Data Type: int64\n", "Column: Rupture of patellar tendon\n", "Data Type: object\n", "Column: Intravenous injection (procedure)\n", "Data Type: object\n", "Column: COVID-19\n", "Data Type: object\n", "Column: Estrogen receptor Ag [Presence] in Breast cancer specimen by Immune stain\n", "Data Type: object\n", "Column: Influenza virus A Ag [Presence] in Nasopharynx by Rapid immunoassay\n", "Data Type: object\n", "Column: MCV [Entitic volume] by Automated count\n", "Data Type: object\n", "Column: Admit to ICU (procedure)\n", "Data Type: object\n", "Column: Suicide risk assessment (procedure)\n", "Data Type: object\n", "Column: Sodium\n", "Data Type: object\n", "Column: pH of Urine by Test strip\n", "Data Type: object\n", "Column: 1 ML Vasopressin (USP) 20 UNT/ML Injection\n", "Data Type: object\n", "Column: Macular edema and retinopathy due to type 2 diabetes mellitus (disorder)\n", "Data Type: object\n", "Column: Prostate specific Ag [Mass/volume] in Serum or Plasma\n", "Data Type: object\n", "Column: Naltrexone hydrochloride 50 MG Oral Tablet\n", "Data Type: object\n", "Column: 24 HR Metformin hydrochloride 500 MG Extended Release Oral Tablet\n", "Data Type: object\n", "Column: Physical examination\n", "Data Type: object\n", "Column: Localized primary osteoarthritis of the hand\n", "Data Type: object\n", "Column: Cholelithiasis\n", "Data Type: object\n", "Column: Progesterone receptor Ag [Presence] in Breast cancer specimen by Immune stain\n", "Data Type: object\n", "Column: Diazepam 5 MG Oral Tablet\n", "Data Type: object\n", "Column: Azithromycin 250 MG Oral Tablet\n", "Data Type: float64\n", "Column: Cyclophosphamide 1000 MG Injection\n", "Data Type: object\n", "Column: 72 HR Fentanyl 0.025 MG/HR Transdermal System\n", "Data Type: object\n", "Column: Appendicitis\n", "Data Type: object\n", "Column: History of cardiac arrest (situation)\n", "Data Type: object\n", "Column: Brachytherapy of breast (procedure)\n", "Data Type: object\n", "Column: Lymphocytes [#/volume] in Blood by Automated count\n", "Data Type: float64\n", "Column: Concussion with loss of consciousness\n", "Data Type: object\n", "Column: Leukocytes [#/volume] in Blood by Automated count\n", "Data Type: object\n", "Column: Home health aide service (regime/therapy)\n", "Data Type: object\n", "Column: Hep A adult\n", "Data Type: object\n", "Column: Hypertriglyceridemia (disorder)\n", "Data Type: object\n", "Column: Erythrocyte distribution width [Ratio] by Automated count\n", "Data Type: object\n", "Column: Glomerular filtration rate/1.73 sq M.predicted\n", "Data Type: object\n", "Column: Colchicine 0.6 MG Oral Tablet\n", "Data Type: object\n", "Column: Nasal congestion (finding)\n", "Data Type: object\n", "Column: Injury of tendon of the rotator cuff of shoulder\n", "Data Type: object\n", "Column: Atropine Sulfate 1 MG/ML Injectable Solution\n", "Data Type: object\n", "Column: Male infertility due to cystic fibrosis (disorder)\n", "Data Type: float64\n", "Column: Posttraumatic stress disorder\n", "Data Type: object\n", "Column: Prostatectomy\n", "Data Type: object\n", "Column: Meperidine Hydrochloride 50 MG Oral Tablet\n", "Data Type: object\n", "Column: Gram positive blood culture panel by Probe in Positive blood culture\n", "Data Type: object\n", "Column: Sepsis (disorder)\n", "Data Type: object\n", "Column: Gout\n", "Data Type: object\n", "Column: Thyrotropin [Units/volume] in Serum or Plasma\n", "Data Type: object\n", "Column: Insulin Lispro 100 UNT/ML Injectable Solution [Humalog]\n", "Data Type: object\n", "Column: Parainfluenza virus 1 RNA [Presence] in Respiratory specimen by NAA with probe detection\n", "Data Type: object\n", "Column: Hemoglobin A1c/Hemoglobin.total in Blood\n", "Data Type: object\n", "Column: Color of Urine\n", "Data Type: object\n", "Column: Placing subject in prone position (procedure)\n", "Data Type: object\n", "Column: Counseling for termination of pregnancy\n", "Data Type: object\n", "Column: Lung volume reduction surgery (procedure)\n", "Data Type: object\n", "Column: 20 ML tocilizumab 20 MG/ML Injection\n", "Data Type: object\n", "Column: Levora 0.15/30 28 Day Pack\n", "Data Type: object\n", "Column: Latex IgE Ab in Serum\n", "Data Type: object\n", "Column: Nitrite [Presence] in Urine by Test strip\n", "Data Type: object\n", "Column: Acute deep venous thrombosis (disorder)\n", "Data Type: object\n", "Column: Magnetic resonance imaging of breast (procedure)\n", "Data Type: object\n", "Column: Acetaminophen 300 MG / Codeine Phosphate 15 MG Oral Tablet\n", "Data Type: object\n", "Column: Fracture of clavicle\n", "Data Type: object\n", "Column: Open Removal of Gall Bladder\n", "Data Type: object\n", "Column: ethnic\n", "Data Type: object\n", "Column: Paclitaxel 100 MG Injection\n", "Data Type: object\n", "Column: 10 ML Fentanyl 0.05 MG/ML Injection\n", "Data Type: object\n", "Column: Chronic neck pain (finding)\n", "Data Type: object\n", "Column: Microalbumin Creatinine Ratio\n", "Data Type: object\n", "Column: Chill (finding)\n", "Data Type: object\n", "Column: Animal dander (substance)\n", "Data Type: object\n", "Column: History of upper limb amputation (situation)\n", "Data Type: float64\n", "Column: Transfer to stepdown unit (procedure)\n", "Data Type: object\n", "Column: Chronic intractable migraine without aura\n", "Data Type: object\n", "Column: Dyspnea (finding)\n", "Data Type: object\n", "Column: 1 ML denosumab 60 MG/ML Prefilled Syringe\n", "Data Type: float64\n", "Column: Stroke\n", "Data Type: object\n", "Column: Chlorpheniramine Maleate 4 MG Oral Tablet\n", "Data Type: object\n", "Column: Drugs of abuse 5 panel - Urine by Screen method\n", "Data Type: object\n", "Column: Admission to neurosurgical department\n", "Data Type: float64\n", "Column: 20 Gene mutation test\n", "Data Type: float64\n", "Column: Abuse-Deterrent 12 HR Oxycodone Hydrochloride 15 MG Extended Release Oral Tablet\n", "Data Type: object\n", "Column: Sputum examination (procedure)\n", "Data Type: object\n", "Column: carvedilol 25 MG Oral Tablet\n", "Data Type: object\n", "Column: Terfenadine 60 MG Oral Tablet\n", "Data Type: object\n", "Column: Removal of endotracheal tube (procedure)\n", "Data Type: object\n", "Column: Abuse-Deterrent 12 HR Oxycodone Hydrochloride 10 MG Extended Release Oral Tablet [Oxycontin]\n", "Data Type: object\n", "Column: Respiratory Disorders\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Heart and Cardiovascular Diseases\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Metabolic and Endocrine Disorders\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Neurological Disorders\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Orthopedic Injuries\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Mental Health\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Reproductive and Pregnancy\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Pain Relievers and Analesics\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Cardiovascular and Blood Pressure\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Injection Medications\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Oral Medications\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Other Medications\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Therapies and Regimes\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Diagnostic Procedures\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Surgical Interventions\n", "Data Type: float64\n", "Data Type: float64\n", "Column: Patient Care Management\n", "Data Type: float64\n", "Data Type: float64\n" ] } ], "source": [ "for col in df2.columns:\n", " # print data type of column\n", " print(f\"Column: {col}\") \n", " print(f\"Data Type: {df2[col].dtype}\")\n", " if col in categories:\n", " # change data type to numeric\n", " df2[col] = pd.to_numeric(df2[col], errors='coerce')\n", " print(f\"Data Type: {df2[col].dtype}\")" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "unimportant_columns = ['race', 'ethnic', 'state', 'Social migrant (finding)', 'Lack of access to transportation (finding)', 'Transport problems (finding)', 'Full-time employment (finding)', 'Face mask (physical object)', 'Childbirth', 'Cesarean section', 'Normal pregnancy', 'Non-low risk pregnancy']\n", "df2.drop(columns=unimportant_columns, inplace=True)\n", "used_columns = respiratory_disorders_columns + heart_and_cardiovascular_diseases_columns + metabolic_and_endocrine_disorders_columns + neurological_disorders_columns + orthopedic_injuries_columns + mental_health_columns + reproductive_and_pregancy_columns + pain_relievers_and_analesics_columns + cardiovascular_and_blood_pressure_medications_columns + injection_medications_columns + oral_medications_columns + other_medications_columns + therapies_and_regimes_columns + diagnostic_procedures_columns + surgerical_interventions_columns + patient_care_management_columns\n", "df2.drop(columns=used_columns, inplace=True)\n", "null_cols_in_train_data = ['Pancreatin 600 MG Oral Tablet',\n", " 'Body mass index 40+ - severely obese (finding)',\n", " '0.67 ML anakinra 149 MG/ML Prefilled Syringe',\n", " 'Oral Glucose Tolerance Test', 'Diabetes from Cystic Fibrosis',\n", " 'Cystic Fibrosis', '20 Gene mutation test',\n", " 'Intravenous infusion (procedure)',\n", " 'History of disarticulation at wrist (situation)', 'Sweat Test',\n", " 'Bee venom (substance)', 'Vancomycin 50 MG/ML Injectable Solution',\n", " 'canagliflozin 100 MG Oral Tablet', 'Intravenous antibiotic therapy',\n", " 'Suicidal deliberate poisoning', 'Take blood sample', 'Lung Transplant',\n", " 'Sepsis caused by Pseudomonas (disorder)',\n", " 'History of upper limb amputation (situation)',\n", " 'Infection caused by Staphylococcus aureus',\n", " 'Incision of trachea (procedure)', 'Sputum Culture',\n", " 'Sepsis caused by Staphylococcus aureus', 'Total replacement of hip']\n", "df2.drop(columns=null_cols_in_train_data, inplace=True)\n", "df2.dropna(axis=1, how='all', inplace=True)" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "df_one_hot = pd.get_dummies(df2['age'], prefix='age')\n", "df2 = pd.concat([df2, df_one_hot], axis=1)\n", "df2['age_30t50'] = df2['age_30t50'].astype(int)\n", "df2['age_50t70'] = df2['age_50t70'].astype(int)\n", "df2['age_gt70'] = df2['age_gt70'].astype(int)\n", "df2.drop(columns=['age'], inplace=True)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "null_value_cols = ['American house dust mite IgE Ab in Serum',\n", " 'Cat dander IgE Ab in Serum',\n", " 'Cladosporium herbarum IgE Ab in Serum',\n", " 'Codfish IgE Ab in Serum',\n", " 'Common Ragweed IgE Ab in Serum',\n", " 'Cow milk IgE Ab in Serum',\n", " 'Egg white IgE Ab in Serum',\n", " 'FEV1/FVC',\n", " 'Honey bee IgE Ab in Serum',\n", " 'Lactate [Mass/volume] in Blood',\n", " 'Latex IgE Ab in Serum',\n", " 'Mean blood pressure',\n", " 'Oxygen Saturation',\n", " 'Peanut IgE Ab in Serum',\n", " 'Shrimp IgE Ab in Serum',\n", " 'Soybean IgE Ab in Serum',\n", " 'Thyrotropin [Units/volume] in Serum or Plasma',\n", " 'Thyroxine (T4) free [Mass/volume] in Serum or Plasma',\n", " 'Walnut IgE Ab in Serum',\n", " 'Wheat IgE Ab in Serum',\n", " 'White oak IgE Ab in Serum']\n", "\n", "df2.drop(columns=null_value_cols, inplace=True)" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "n_abn_columns = []\n", "for col in df2.columns:\n", " if df2[col].isin(['normal', 'abnormal']).any():\n", " n_abn_columns.append(col)" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "n_abn_columns = [col for col in n_abn_columns if col not in null_value_cols]\n", "df2 = pd.get_dummies(df2, columns=n_abn_columns, prefix_sep='_', dtype=int)" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "columns_to_encode = [\n", " 'HER2 [Presence] in Breast cancer specimen by FISH',\n", " 'Parainfluenza virus 1 RNA [Presence] in Respiratory specimen by NAA with probe detection',\n", " 'Estrogen+Progesterone receptor Ag [Presence] in Tissue by Immune stain',\n", " 'Ketones [Mass/volume] in Urine by Test strip',\n", " 'marital',\n", " 'Abuse Status [OMAHA]',\n", " 'Interleukin 6 [Mass/volume] in Serum or Plasma',\n", " 'Progesterone receptor Ag [Presence] in Breast cancer specimen by Immune stain',\n", " 'Influenza virus A RNA [Presence] in Respiratory specimen by NAA with probe detection',\n", " 'Parainfluenza virus 2 RNA [Presence] in Respiratory specimen by NAA with probe detection',\n", " 'Response to cancer treatment',\n", " 'Estrogen receptor Ag [Presence] in Breast cancer specimen by Immune stain',\n", " 'Hemoglobin [Presence] in Urine by Test strip',\n", " 'Housing status',\n", " 'Influenza virus B RNA [Presence] in Respiratory specimen by NAA with probe detection',\n", " 'Objective assessment of cardiovascular disease NYHA',\n", " 'Drugs of abuse 5 panel - Urine by Screen method',\n", " 'Leukocyte esterase [Presence] in Urine by Test strip',\n", " 'Adenovirus A+B+C+D+E DNA [Presence] in Respiratory specimen by NAA with probe detection',\n", " 'Protein [Presence] in Urine by Test strip',\n", " 'Appearance of Urine',\n", " 'Capillary refill [Time] of Nail bed',\n", " 'Treatment status Cancer',\n", " 'Gram positive blood culture panel by Probe in Positive blood culture',\n", " 'Glucose [Presence] in Urine by Test strip',\n", " 'Respiratory syncytial virus RNA [Presence] in Respiratory specimen by NAA with probe detection',\n", " 'Functional capacity NYHA',\n", " 'Color of Urine',\n", " 'Nitrite [Presence] in Urine by Test strip',\n", " 'Tumor marker Cancer',\n", " 'Tobacco smoking status NHIS',\n", " 'gender',\n", " 'HIV status',\n", " 'Are you covered by health insurance or some other kind of health care plan [PhenX]',\n", " 'Human metapneumovirus RNA [Presence] in Respiratory specimen by NAA with probe detection',\n", " 'Ketones [Presence] in Urine by Test strip',\n", " 'Clarity of Urine',\n", " 'Stage group.clinical Cancer',\n", " 'Rhinovirus RNA [Presence] in Respiratory specimen by NAA with probe detection',\n", " 'HER2 [Presence] in Breast cancer specimen by Immune stain',\n", " 'Smokes tobacco daily'\n", "]\n", "\n", "\n", "df2 = pd.get_dummies(df2, columns=columns_to_encode, prefix_sep='_', dtype=int)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "import json\n", "\n", "with open('medians.json') as f:\n", " medians = json.load(f)\n", "\n", "df2 = df2.fillna(medians)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "X_train = pd.read_csv('../transformed_data/X_train.csv')\n", "y_train = pd.read_csv('../transformed_data/y_train.csv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Testing models" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "X_val = df2.drop('label', axis=1)\n", "y_val = df2['label']" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": [ "from tabulate import tabulate\n", "from sklearn.metrics import accuracy_score, recall_score, precision_score, f1_score, roc_auc_score\n", "def calculate_metrics(model, X_train, y_train, X_val, y_val):\n", " model.fit(X_train, y_train)\n", " predictions = model.predict(X_val)\n", " accuracy = accuracy_score(y_val, predictions)\n", " recall = recall_score(y_val, predictions)\n", " precision = precision_score(y_val, predictions)\n", " f1 = f1_score(y_val, predictions)\n", " auc = roc_auc_score(y_val, model.predict_proba(X_val)[:, 1])\n", " gini = 2 * auc - 1\n", " return accuracy, recall, precision, f1, auc, gini\n", "\n", "def print_metrics(models, X_train, y_train, X_val, y_val):\n", " results = pd.DataFrame(columns=['Model', 'Accuracy', 'Recall', 'Precision', 'F1 Score', 'AUC', 'Gini'])\n", " for model in models:\n", " accuracy, recall, precision, f1, auc, gini = calculate_metrics(model, X_train, y_train, X_val, y_val)\n", " results.loc[len(results)] = {'Model': model.__class__.__name__,\n", " 'Accuracy': accuracy,\n", " 'Recall': recall,\n", " 'Precision': precision,\n", " 'F1 Score': f1,\n", " 'AUC': auc,\n", " 'Gini': gini}\n", " print(tabulate(results, headers='keys', tablefmt='simple'))" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.neural_network import MLPClassifier\n", "from sklearn.naive_bayes import GaussianNB, BernoulliNB, MultinomialNB, ComplementNB\n", "from sklearn.ensemble import GradientBoostingClassifier, AdaBoostClassifier, RandomForestClassifier\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.svm import SVC\n", "from sklearn.neighbors import KNeighborsClassifier\n", "from sklearn.ensemble import ExtraTreesClassifier, BaggingClassifier\n", "from sklearn.naive_bayes import GaussianNB" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": [ "models = [DecisionTreeClassifier(), \n", " MLPClassifier(),\n", " GaussianNB(), \n", " GradientBoostingClassifier(), \n", " AdaBoostClassifier(),\n", " RandomForestClassifier(),\n", " LogisticRegression(),\n", " SVC(probability=True),\n", " KNeighborsClassifier(),\n", " ExtraTreesClassifier(),\n", " BaggingClassifier(),\n", " BernoulliNB()\n", " ]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What columns are in X_val and not in X_train?" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Interleukin 6 [Mass/volume] in Serum or Plasma_13.54\n" ] } ], "source": [ "for col in X_val.columns:\n", " if col not in X_train.columns:\n", " print(col)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is a column created by one hot encoding, we will drop it." ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "X_val.drop(columns=['Interleukin 6 [Mass/volume] in Serum or Plasma_13.54'], inplace=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What columns are in X_train and not in X_val?" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Interleukin 6 [Mass/volume] in Serum or Plasma_5.33\n", "Ketones [Presence] in Urine by Test strip_2+\n" ] } ], "source": [ "for col in X_train.columns:\n", " if col not in X_val.columns:\n", " print(col)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These are also columns created by one hot encoding, we will add them to X_val." ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [], "source": [ "X_val['Interleukin 6 [Mass/volume] in Serum or Plasma_13.54'] = 0\n", "X_val['Ketones [Presence] in Urine by Test strip_2+'] = 0 " ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(222, 222)" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(X_train.columns), len(X_val.columns)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "After this, we will have the same columns in X_train and X_val. We can now try to predict the target variable." ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training data\n", " Model Accuracy Recall Precision F1 Score AUC Gini\n", "-- -------------------------- ---------- -------- ----------- ---------- -------- --------\n", " 0 DecisionTreeClassifier 1 1 1 1 1 1\n", " 1 MLPClassifier 0.98099 0.988636 0.939369 0.963373 0.998721 0.997442\n", " 2 GaussianNB 0.636494 0.982517 0.40895 0.577521 0.7541 0.5082\n", " 3 GradientBoostingClassifier 0.994474 0.982955 0.995133 0.989006 0.999592 0.999184\n", " 4 AdaBoostClassifier 0.9916 0.975524 0.991119 0.98326 0.999616 0.999232\n", " 5 RandomForestClassifier 1 1 1 1 1 1\n", " 6 LogisticRegression 0.984527 0.961101 0.977333 0.969149 0.997157 0.994314\n", " 7 SVC 0.946618 0.788899 1 0.881994 0.96298 0.925961\n", " 8 KNeighborsClassifier 0.979111 0.922203 0.994814 0.957133 0.998972 0.997945\n", " 9 ExtraTreesClassifier 1 1 1 1 1 1\n", "10 BaggingClassifier 0.998232 0.994318 0.998683 0.996496 0.999991 0.999983\n", "11 BernoulliNB 0.752431 0.970717 0.505462 0.664771 0.965899 0.931798\n" ] } ], "source": [ "print('Training data')\n", "print_metrics(models, X_train, y_train, X_train, y_train)" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Validation data\n", " Model Accuracy Recall Precision F1 Score AUC Gini\n", "-- -------------------------- ---------- -------- ----------- ---------- -------- -----------\n", " 0 DecisionTreeClassifier 0.259603 1 0.255959 0.407591 0.503286 0.00657212\n", " 1 MLPClassifier 0.254705 1 0.254705 0.406 0.753141 0.506282\n", " 2 GaussianNB 0.745295 0 0 0 0.5 0\n", " 3 GradientBoostingClassifier 0.259603 1 0.255959 0.407591 0.498713 -0.00257395\n", " 4 AdaBoostClassifier 0.324826 1 0.273912 0.430033 0.783435 0.56687\n", " 5 RandomForestClassifier 0.282031 0.998988 0.261734 0.414793 0.97158 0.943161\n", " 6 LogisticRegression 0.745295 0 0 0 0.923673 0.847346\n", " 7 SVC 0.260892 1 0.256291 0.408012 0.965635 0.931271\n", " 8 KNeighborsClassifier 0.745295 0 0 0 0.5 0\n", " 9 ExtraTreesClassifier 0.792214 0.92004 0.555623 0.692835 0.948349 0.896698\n", "10 BaggingClassifier 0.259603 1 0.255959 0.407591 0.503286 0.00657212\n", "11 BernoulliNB 0.803815 0.558704 0.629418 0.591957 0.802888 0.605775\n" ] } ], "source": [ "print('Validation data')\n", "print_metrics(models, X_train, y_train, X_val, y_val)" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [], "source": [ "from matplotlib import pyplot as plt\n", "from sklearn import metrics\n", "def roc_curve_plot(models, X_train, y_train, X_val, y_val):\n", " plt.figure(0).clf()\n", " plt.figure(figsize=(8, 8))\n", " plt.title(\"ROC Curve for Different Models (Validation Data)\")\n", " for model in models:\n", " model.fit(X_train, y_train)\n", " y_pred = model.predict_proba(X_val)[:, 1]\n", " fpr, tpr, _ = metrics.roc_curve(y_val, y_pred)\n", " auc = round(metrics.roc_auc_score(y_val, y_pred), 4)\n", " model_name = model.__class__.__name__ \n", " if model_name == 'Pipeline':\n", " model_name = model['model'].__class__.__name__\n", " plt.plot(fpr, tpr, label=f\"{model_name}, AUC={auc}\")\n", " plt.legend(framealpha=0.0)" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "roc_curve_plot(models, X_train, y_train, X_val, y_val)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The most important scores are recall and AUC, so currently the best models seem to be:\n", "- ExtraTreesClassifier (recall = 0.92004, AUC = 0.948349, very good performance in every metric)\n", "
\n", "
\n", "Models with recall = 1 have poor accuracy, so we will not use them." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "base", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.12" } }, "nbformat": 4, "nbformat_minor": 2 }