This project was built by Veronica Latzinnik and Almog Elharar at:
This project was done as part of our B.Sc studies at Tel-Aviv University, Sagol school of neuroscience. It is a decision support system for ICU, that uses XGBoost to predict mortality rates of patients based on different measured features as well as clustering the patients, potentially aiding in choosing treatment.
The project was built using JS(Angular), Flask, and MongoDB. all backend code was written in Python 3.6
The project structure is as follows:
'/' contains 'app.py' script to deploy flask server, as well as all python files necessary to serve requests from the client, and handle data on a regular basis.
'/static' contains all front-end code i.e. all HTML templates, JavaScript files and static content
'/backend' contains all data files - archives and daily recieved data from the hospital
'/templates/index.html is the main template and the root of the web-app