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/src/preprocess/05_data_split.ipynb
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| a | b/src/preprocess/05_data_split.ipynb | ||
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| 1 | { |
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| 2 | "cells": [ |
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| 3 | { |
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| 4 | "cell_type": "code", |
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| 5 | "id": "debdace9", |
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| 6 | "metadata": {}, |
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| 7 | "source": [ |
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| 8 | "import os\n", |
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| 9 | "import sys\n", |
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| 10 | "\n", |
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| 11 | "src_path = os.path.abspath(\"../..\")\n", |
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| 12 | "print(src_path)\n", |
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| 13 | "sys.path.append(src_path)" |
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| 14 | ], |
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| 15 | "outputs": [], |
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| 16 | "execution_count": null |
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| 17 | }, |
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| 18 | { |
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| 19 | "cell_type": "code", |
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| 20 | "id": "6bad1e09", |
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| 21 | "metadata": {}, |
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| 22 | "source": [ |
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| 23 | "from src.utils import create_directory, raw_data_path, processed_data_path, set_seed" |
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| 24 | ], |
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| 25 | "outputs": [], |
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| 26 | "execution_count": null |
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| 27 | }, |
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| 28 | { |
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| 29 | "cell_type": "code", |
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| 30 | "id": "5d9bc78c", |
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| 31 | "metadata": {}, |
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| 32 | "source": [ |
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| 33 | "set_seed(seed=42)" |
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| 34 | ], |
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| 35 | "outputs": [], |
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| 36 | "execution_count": null |
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| 37 | }, |
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| 38 | { |
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| 39 | "cell_type": "code", |
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| 40 | "id": "13d22a57", |
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| 41 | "metadata": {}, |
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| 42 | "source": [ |
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| 43 | "import pandas as pd" |
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| 44 | ], |
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| 45 | "outputs": [], |
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| 46 | "execution_count": null |
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| 47 | }, |
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| 48 | { |
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| 49 | "cell_type": "code", |
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| 50 | "id": "dd9852d5", |
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| 51 | "metadata": {}, |
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| 52 | "source": [ |
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| 53 | "mimic_iv_path = os.path.join(raw_data_path, \"physionet.org/files/mimiciv/2.2\")\n", |
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| 54 | "output_path = os.path.join(processed_data_path, \"mimic4\")" |
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| 55 | ], |
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| 56 | "outputs": [], |
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| 57 | "execution_count": null |
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| 58 | }, |
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| 59 | { |
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| 60 | "cell_type": "code", |
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| 61 | "id": "b6a27998", |
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| 62 | "metadata": {}, |
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| 63 | "source": [ |
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| 64 | "cohort = pd.read_csv(os.path.join(output_path, \"cohort+len.csv\"))\n", |
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| 65 | "print(cohort.shape)\n", |
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| 66 | "cohort.head()" |
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| 67 | ], |
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| 68 | "outputs": [], |
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| 69 | "execution_count": null |
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| 70 | }, |
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| 71 | { |
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| 72 | "cell_type": "code", |
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| 73 | "id": "9dd92e23", |
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| 74 | "metadata": {}, |
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| 75 | "source": [ |
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| 76 | "cohort[\"hadm_intime\"] = pd.to_datetime(cohort[\"hadm_intime\"])\n", |
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| 77 | "cohort[\"hadm_outtime\"] = pd.to_datetime(cohort[\"hadm_outtime\"])\n", |
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| 78 | "cohort[\"stay_intime\"] = pd.to_datetime(cohort[\"stay_intime\"])\n", |
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| 79 | "cohort[\"stay_outtime\"] = pd.to_datetime(cohort[\"stay_outtime\"])" |
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| 80 | ], |
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| 81 | "outputs": [], |
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| 82 | "execution_count": null |
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| 83 | }, |
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| 84 | { |
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| 85 | "cell_type": "code", |
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| 86 | "id": "8f55c793", |
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| 87 | "metadata": {}, |
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| 88 | "source": [ |
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| 89 | "hadm_ids = set(cohort.hadm_id.unique().tolist())\n", |
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| 90 | "len(hadm_ids)" |
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| 91 | ], |
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| 92 | "outputs": [], |
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| 93 | "execution_count": null |
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| 94 | }, |
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| 95 | { |
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| 96 | "cell_type": "code", |
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| 97 | "id": "26459eda", |
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| 98 | "metadata": {}, |
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| 99 | "source": [ |
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| 100 | "import ast\n", |
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| 101 | "import numpy as np\n", |
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| 102 | "\n", |
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| 103 | "\n", |
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| 104 | "def safe_literal_eval(s):\n", |
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| 105 | " if pd.isna(s):\n", |
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| 106 | " return np.nan\n", |
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| 107 | " return ast.literal_eval(s)\n", |
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| 108 | "\n", |
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| 109 | "\n", |
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| 110 | "cohort.label_diagnosis = cohort.label_diagnosis.apply(safe_literal_eval)" |
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| 111 | ], |
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| 112 | "outputs": [], |
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| 113 | "execution_count": null |
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| 114 | }, |
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| 115 | { |
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| 116 | "cell_type": "code", |
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| 117 | "id": "99d2b8c8", |
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| 118 | "metadata": {}, |
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| 119 | "source": [ |
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| 120 | "qa_note = pd.read_json(os.path.join(output_path, \"qa_note.jsonl\"), lines = True)\n", |
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| 121 | "qa_note" |
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| 122 | ], |
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| 123 | "outputs": [], |
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| 124 | "execution_count": null |
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| 125 | }, |
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| 126 | { |
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| 127 | "cell_type": "code", |
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| 128 | "id": "741b6ed7", |
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| 129 | "metadata": {}, |
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| 130 | "source": [ |
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| 131 | "qa_note.hadm_id.nunique()" |
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| 132 | ], |
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| 133 | "outputs": [], |
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| 134 | "execution_count": null |
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| 135 | }, |
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| 136 | { |
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| 137 | "cell_type": "code", |
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| 138 | "id": "7d287db0", |
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| 139 | "metadata": {}, |
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| 140 | "source": [ |
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| 141 | "qa_event = pd.read_json(os.path.join(output_path, \"qa_event.jsonl\"), lines = True)\n", |
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| 142 | "qa_event" |
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| 143 | ], |
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| 144 | "outputs": [], |
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| 145 | "execution_count": null |
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| 146 | }, |
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| 147 | { |
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| 148 | "cell_type": "code", |
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| 149 | "id": "dbc2af95", |
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| 150 | "metadata": {}, |
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| 151 | "source": [ |
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| 152 | "qa_event.hadm_id.nunique()" |
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| 153 | ], |
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| 154 | "outputs": [], |
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| 155 | "execution_count": null |
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| 156 | }, |
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| 157 | { |
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| 158 | "cell_type": "code", |
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| 159 | "id": "b4bd715e", |
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| 160 | "metadata": {}, |
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| 161 | "source": [ |
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| 162 | "qa_event.event_type.value_counts()" |
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| 163 | ], |
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| 164 | "outputs": [], |
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| 165 | "execution_count": null |
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| 166 | }, |
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| 167 | { |
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| 168 | "cell_type": "markdown", |
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| 169 | "id": "5a9d60c6", |
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| 170 | "metadata": {}, |
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| 171 | "source": [ |
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| 172 | "helper" |
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| 173 | ] |
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| 174 | }, |
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| 175 | { |
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| 176 | "cell_type": "code", |
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| 177 | "id": "5171bbae", |
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| 178 | "metadata": {}, |
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| 179 | "source": [ |
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| 180 | "from concurrent.futures import ThreadPoolExecutor\n", |
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| 181 | "from tqdm import tqdm\n", |
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| 182 | "from pandarallel import pandarallel" |
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| 183 | ], |
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| 184 | "outputs": [], |
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| 185 | "execution_count": null |
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| 186 | }, |
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| 187 | { |
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| 188 | "cell_type": "code", |
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| 189 | "id": "5d6b9ce2", |
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| 190 | "metadata": {}, |
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| 191 | "source": [ |
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| 192 | "pandarallel.initialize(progress_bar=True)" |
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| 193 | ], |
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| 194 | "outputs": [], |
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| 195 | "execution_count": null |
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| 196 | }, |
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| 197 | { |
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| 198 | "cell_type": "markdown", |
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| 199 | "id": "941b116b", |
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| 200 | "metadata": {}, |
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| 201 | "source": [ |
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| 202 | "stat" |
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| 203 | ] |
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| 204 | }, |
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| 205 | { |
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| 206 | "cell_type": "code", |
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| 207 | "id": "503a9cbd", |
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| 208 | "metadata": {}, |
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| 209 | "source": [ |
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| 210 | "cohort = cohort[cohort.hadm_id.isin(qa_note.hadm_id.unique())]\n", |
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| 211 | "len(cohort)" |
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| 212 | ], |
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| 213 | "outputs": [], |
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| 214 | "execution_count": null |
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| 215 | }, |
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| 216 | { |
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| 217 | "cell_type": "code", |
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| 218 | "id": "b4e602ba", |
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| 219 | "metadata": {}, |
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| 220 | "source": [ |
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| 221 | "cohort = cohort[cohort.hadm_id.isin(qa_event.hadm_id.unique())]\n", |
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| 222 | "len(cohort)" |
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| 223 | ], |
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| 224 | "outputs": [], |
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| 225 | "execution_count": null |
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| 226 | }, |
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| 227 | { |
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| 228 | "cell_type": "code", |
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| 229 | "id": "5014c99f", |
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| 230 | "metadata": { |
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| 231 | "scrolled": false |
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| 232 | }, |
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| 233 | "source": [ |
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| 234 | "cohort.hadm_los.describe(percentiles=[.1, .25, .5, .75, .9, .95, .99])" |
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| 235 | ], |
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| 236 | "outputs": [], |
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| 237 | "execution_count": null |
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| 238 | }, |
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| 239 | { |
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| 240 | "cell_type": "code", |
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| 241 | "id": "11f5935f", |
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| 242 | "metadata": {}, |
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| 243 | "source": [ |
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| 244 | "548.490833 / 24" |
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| 245 | ], |
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| 246 | "outputs": [], |
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| 247 | "execution_count": null |
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| 248 | }, |
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| 249 | { |
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| 250 | "cell_type": "code", |
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| 251 | "id": "87a1b947", |
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| 252 | "metadata": {}, |
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| 253 | "source": [ |
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| 254 | "cohort.stay_los.describe(percentiles=[.1, .25, .5, .75, .9, .95, .99])" |
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| 255 | ], |
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| 256 | "outputs": [], |
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| 257 | "execution_count": null |
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| 258 | }, |
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| 259 | { |
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| 260 | "cell_type": "code", |
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| 261 | "id": "f774a307", |
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| 262 | "metadata": {}, |
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| 263 | "source": [ |
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| 264 | "265.649889 / 24" |
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| 265 | ], |
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| 266 | "outputs": [], |
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| 267 | "execution_count": null |
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| 268 | }, |
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| 269 | { |
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| 270 | "cell_type": "code", |
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| 271 | "id": "99d6a2f0", |
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| 272 | "metadata": {}, |
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| 273 | "source": [ |
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| 274 | "cohort.len_selected.describe(percentiles=[.1, .25, .5, .75, .9, .95, .99])" |
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| 275 | ], |
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| 276 | "outputs": [], |
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| 277 | "execution_count": null |
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| 278 | }, |
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| 279 | { |
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| 280 | "cell_type": "code", |
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| 281 | "id": "622669a8", |
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| 282 | "metadata": {}, |
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| 283 | "source": [ |
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| 284 | "cohort_filtered = cohort[cohort.len_selected <= 1256.650000]\n", |
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| 285 | "cohort_filtered" |
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| 286 | ], |
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| 287 | "outputs": [], |
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| 288 | "execution_count": null |
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| 289 | }, |
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| 290 | { |
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| 291 | "cell_type": "code", |
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| 292 | "id": "75ddbce8", |
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| 293 | "metadata": {}, |
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| 294 | "source": [ |
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| 295 | "cohort_filtered.hadm_los.describe(percentiles=[.1, .25, .5, .75, .9, .95, .99])" |
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| 296 | ], |
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| 297 | "outputs": [], |
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| 298 | "execution_count": null |
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| 299 | }, |
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| 300 | { |
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| 301 | "cell_type": "code", |
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| 302 | "id": "aaed6fb7", |
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| 303 | "metadata": {}, |
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| 304 | "source": [ |
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| 305 | "cohort_filtered.stay_los.describe(percentiles=[.1, .25, .5, .75, .9, .95, .99])" |
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| 306 | ], |
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| 307 | "outputs": [], |
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| 308 | "execution_count": null |
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| 309 | }, |
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| 310 | { |
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| 311 | "cell_type": "code", |
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| 312 | "id": "e2cca302", |
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| 313 | "metadata": {}, |
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| 314 | "source": [ |
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| 315 | "cohort_filtered.len_selected.describe(percentiles=[.1, .25, .5, .75, .9, .95, .99])" |
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| 316 | ], |
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| 317 | "outputs": [], |
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| 318 | "execution_count": null |
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| 319 | }, |
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| 320 | { |
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| 321 | "cell_type": "code", |
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| 322 | "id": "bc283fd9", |
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| 323 | "metadata": {}, |
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| 324 | "source": [ |
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| 325 | "all_patients = cohort_filtered.subject_id.unique()\n", |
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| 326 | "len(all_patients)" |
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| 327 | ], |
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| 328 | "outputs": [], |
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| 329 | "execution_count": null |
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| 330 | }, |
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| 331 | { |
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| 332 | "cell_type": "code", |
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| 333 | "id": "18aa0954", |
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| 334 | "metadata": {}, |
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| 335 | "source": [ |
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| 336 | "from sklearn.model_selection import train_test_split\n", |
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| 337 | "\n", |
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| 338 | "\n", |
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| 339 | "train_val_patients, test_patients = train_test_split(all_patients, test_size=0.1, random_state=42)\n", |
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| 340 | "train_patients, val_patients = train_test_split(all_patients, test_size=0.111, random_state=42)" |
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| 341 | ], |
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| 342 | "outputs": [], |
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| 343 | "execution_count": null |
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| 344 | }, |
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| 345 | { |
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| 346 | "cell_type": "code", |
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| 347 | "id": "d5d0a3ac", |
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| 348 | "metadata": {}, |
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| 349 | "source": [ |
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| 350 | "print(train_patients.shape)\n", |
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| 351 | "print(val_patients.shape)\n", |
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| 352 | "print(test_patients.shape)" |
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| 353 | ], |
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| 354 | "outputs": [], |
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| 355 | "execution_count": null |
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| 356 | }, |
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| 357 | { |
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| 358 | "cell_type": "code", |
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| 359 | "id": "57dc6d8f", |
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| 360 | "metadata": {}, |
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| 361 | "source": [ |
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| 362 | "train = cohort_filtered[cohort_filtered.subject_id.isin(train_patients)].reset_index(drop=True)\n", |
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| 363 | "val = cohort_filtered[cohort_filtered.subject_id.isin(val_patients)].reset_index(drop=True)\n", |
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| 364 | "test = cohort_filtered[cohort_filtered.subject_id.isin(test_patients)].reset_index(drop=True)" |
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| 365 | ], |
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| 366 | "outputs": [], |
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| 367 | "execution_count": null |
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| 368 | }, |
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| 369 | { |
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| 370 | "cell_type": "code", |
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| 371 | "id": "860d6a39", |
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| 372 | "metadata": {}, |
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| 373 | "source": [ |
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| 374 | "print(train.shape)\n", |
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| 375 | "print(val.shape)\n", |
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| 376 | "print(test.shape)" |
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| 377 | ], |
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| 378 | "outputs": [], |
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| 379 | "execution_count": null |
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| 380 | }, |
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| 381 | { |
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| 382 | "cell_type": "code", |
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| 383 | "id": "ce3c7f18", |
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| 384 | "metadata": {}, |
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| 385 | "source": [ |
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| 386 | "train.to_csv(os.path.join(output_path, \"cohort_train.csv\"), index=False)\n", |
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| 387 | "val.to_csv(os.path.join(output_path, \"cohort_val.csv\"), index=False)\n", |
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| 388 | "test.to_csv(os.path.join(output_path, \"cohort_test.csv\"), index=False)" |
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| 389 | ], |
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| 390 | "outputs": [], |
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| 391 | "execution_count": null |
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| 392 | }, |
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| 393 | { |
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| 394 | "cell_type": "code", |
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| 395 | "id": "7b0ea788", |
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| 396 | "metadata": {}, |
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| 397 | "source": [ |
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| 398 | "_, test_subset_patients = train_test_split(test_patients, test_size=100, random_state=42)\n", |
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| 399 | "len(test_subset_patients)" |
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| 400 | ], |
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| 401 | "outputs": [], |
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| 402 | "execution_count": null |
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| 403 | }, |
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| 404 | { |
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| 405 | "cell_type": "code", |
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| 406 | "id": "5ba82c66", |
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| 407 | "metadata": {}, |
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| 408 | "source": [ |
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| 409 | "test_subset = test[test.subject_id.isin(test_subset_patients)].groupby(\"subject_id\").apply(lambda x: x.sample(1)).reset_index(drop=True)\n", |
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| 410 | "test_subset" |
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| 411 | ], |
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| 412 | "outputs": [], |
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| 413 | "execution_count": null |
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| 414 | }, |
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| 415 | { |
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| 416 | "metadata": {}, |
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| 417 | "cell_type": "code", |
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| 418 | "source": "test_subset.len_selected.describe()", |
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| 419 | "id": "0bd73438", |
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| 420 | "outputs": [], |
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| 421 | "execution_count": null |
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| 422 | }, |
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| 423 | { |
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| 424 | "cell_type": "code", |
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| 425 | "id": "a58143a2", |
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| 426 | "metadata": {}, |
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| 427 | "source": [ |
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| 428 | "print(test_subset.subject_id.nunique())\n", |
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| 429 | "print(test_subset.hadm_id.nunique())" |
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| 430 | ], |
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| 431 | "outputs": [], |
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| 432 | "execution_count": null |
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| 433 | }, |
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| 434 | { |
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| 435 | "cell_type": "code", |
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| 436 | "id": "745f82b5", |
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| 437 | "metadata": {}, |
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| 438 | "source": [ |
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| 439 | "test_subset.to_csv(os.path.join(output_path, \"cohort_test_subset.csv\"), index=False)" |
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| 440 | ], |
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| 441 | "outputs": [], |
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| 442 | "execution_count": null |
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| 443 | }, |
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| 444 | { |
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| 445 | "cell_type": "code", |
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| 446 | "id": "7ba15669", |
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| 447 | "metadata": {}, |
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| 448 | "source": [ |
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| 449 | "qa_note_test_subset = qa_note[qa_note.hadm_id.isin(test_subset.hadm_id.unique())]\n", |
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| 450 | "qa_note_test_subset" |
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| 451 | ], |
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| 452 | "outputs": [], |
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| 453 | "execution_count": null |
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| 454 | }, |
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| 455 | { |
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| 456 | "cell_type": "code", |
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| 457 | "id": "040ce4fb", |
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| 458 | "metadata": {}, |
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| 459 | "source": [ |
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| 460 | "qa_event_test_subset = qa_event[qa_event.hadm_id.isin(test_subset.hadm_id.unique())].groupby(\"hadm_id\").apply(lambda x: x.sample(1)).reset_index(drop=True)\n", |
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| 461 | "qa_event_test_subset" |
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| 462 | ], |
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| 463 | "outputs": [], |
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| 464 | "execution_count": null |
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| 465 | }, |
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| 466 | { |
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| 467 | "cell_type": "code", |
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| 468 | "id": "5455dbca", |
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| 469 | "metadata": {}, |
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| 470 | "source": [ |
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| 471 | "qa_event_test_subset.hadm_id.nunique()" |
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| 472 | ], |
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| 473 | "outputs": [], |
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| 474 | "execution_count": null |
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| 475 | }, |
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| 476 | { |
||
| 477 | "cell_type": "code", |
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| 478 | "id": "4c78aa45", |
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| 479 | "metadata": {}, |
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| 480 | "source": [ |
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| 481 | "qa_event_test_subset.event_type.value_counts()" |
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| 482 | ], |
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| 483 | "outputs": [], |
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| 484 | "execution_count": null |
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| 485 | }, |
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| 486 | { |
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| 487 | "cell_type": "code", |
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| 488 | "id": "9942e684", |
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| 489 | "metadata": {}, |
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| 490 | "source": [ |
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| 491 | "qa_test_subset = pd.concat([qa_event_test_subset, qa_note_test_subset]).reset_index(drop=True)\n", |
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| 492 | "qa_test_subset" |
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| 493 | ], |
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| 494 | "outputs": [], |
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| 495 | "execution_count": null |
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| 496 | }, |
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| 497 | { |
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| 498 | "cell_type": "code", |
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| 499 | "id": "8366ae94", |
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| 500 | "metadata": {}, |
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| 501 | "source": [ |
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| 502 | "qa_test_subset.to_csv(os.path.join(output_path, \"qa_test_subset.csv\"), index=False)" |
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| 503 | ], |
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| 504 | "outputs": [], |
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| 505 | "execution_count": null |
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| 506 | }, |
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| 507 | { |
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| 508 | "cell_type": "code", |
||
| 509 | "id": "410a34c3", |
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| 510 | "metadata": {}, |
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| 511 | "source": [], |
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| 512 | "outputs": [], |
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| 513 | "execution_count": null |
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| 514 | } |
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| 515 | ], |
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| 516 | "metadata": { |
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| 517 | "kernelspec": { |
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| 518 | "display_name": "pytorch20", |
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| 519 | "language": "python", |
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| 520 | "name": "pytorch20" |
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| 521 | }, |
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| 522 | "language_info": { |
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| 523 | "codemirror_mode": { |
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| 524 | "name": "ipython", |
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| 525 | "version": 3 |
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| 526 | }, |
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| 527 | "file_extension": ".py", |
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| 528 | "mimetype": "text/x-python", |
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| 529 | "name": "python", |
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| 530 | "nbconvert_exporter": "python", |
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| 531 | "pygments_lexer": "ipython3", |
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| 532 | "version": "3.9.19" |
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| 533 | } |
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| 534 | }, |
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| 535 | "nbformat": 4, |
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| 536 | "nbformat_minor": 5 |
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| 537 | } |