Patients_Cancerous_Stage_Detection_and_Treatment_Suggestion_using_Random_Forest_Technique_ML
Patients Cancerous Stage Detection & Treatment suggestion
There are a variety of options available for cancer treatment. The type of treatment recommended for an individual is influenced by various factors such as cancer-type, the severity of a cancer (stage) and most important the genetic heterogeneity. In such a complex environment, the targeted drug treatments are likely to be irresponsive or respond differently. To study anti-cancer drug response we need to understand cancerous profiles. These cancerous profiles carry information which can reveal the underlying factors responsible for cancer growth. Hence, there is need to analyze cancer data for predicting optimal treatment options. Analysis of such profiles can help to predict and discover potential drug targets and drugs. In this paper the main aim is to provide machine learning based classification technique for cancerous profiles.
we achieved near to 100% Accuracy on Random Forest & SVM techniques
SVM
"text": [
" precision recall f1-score support\n",
"\n",
" 0 1.00 1.00 1.00 67\n",
" 1 1.00 1.00 1.00 75\n",
" 2 1.00 1.00 1.00 58\n",
"\n",
" accuracy 1.00 200\n",
" macro avg 1.00 1.00 1.00 200\n",
"weighted avg 1.00 1.00 1.00 200\n",
Random Forest Classifier
"text": [
" precision recall f1-score support\n",
"\n",
" 0 1.00 1.00 1.00 67\n",
" 1 1.00 1.00 1.00 75\n",
" 2 1.00 1.00 1.00 58\n",
"\n",
" accuracy 1.00 200\n",
" macro avg 1.00 1.00 1.00 200\n",
"weighted avg 1.00 1.00 1.00 200\n",
Base Paper
Classification of Cancerous Profiles Using Machine Learning.pdf
Installations (# modules Installations process
( 1-open "anaconda prompt/ command prompt",
2-type&enter: activate tsf,
3-type&enter command: pip install module-name)
'''modules names below''')
flask
numpy
webbrowser
warnings
pickle
sklearn
pandas
matplotlib
RUN PROCESS
1) search & open "anaconda prompt/ command prompt"
2) type & enter "cd your-code-location-folder"
3) type & enter "python app.py"
WORKING VIDEO
Watch Now