Medic

Improving Lives Together.

The problem Medic solves

During this pandemic, many hospitals are taking advantage of people's need of hospitals to get proper treatment and are quoting extremely high prices to the patients which is totally unjust. What Medic does is that it provides the patient with a transparent data such as the prices, availability of beds, oxygen and ventilator availability of all the hospitals in their locality so that the user can compare the expenses and the recovery rate of all the hospitals and choose what's best for them.

Challenges we ran into

The major hurdle on the web development side was to configure the webapp with both firebase and flask and plotting graphs was also a hurdle as the Chart.js library was not upto the mark. Hosting the Flask API on various cloud services caused a problem. We tried it on various platforms such as Heroku, DigitialOcean and Linode. Dataset generation was a problem Configuring the graph data using the API was a challenge.

Features offered by Medic

Real Time predictions of Hospital Data
- Using 'PyTorch' model to predict hospital data of the next day.
Hospital Side Web Application
- An interface for the hospital to update data from its database and also add and update patient medical history.
Patient Side App
- An interface for a patient to browse through nearby hospitals and select a hospital based on its performance, also observe his/her medical history live.

Technology Stack and Dependencies

ML
- pytorch
- numpy
- pandas
- scikit-learn
APIs
- Firebase
- Flask
Front-end
- Ionic Framework with React
- React Native for the patient's app
- Chart.js API

How to setup dev environment

git clone repo link

Website
- cd hospital_side
- npm install
- ionic serve
App
- cd patient_side
- yarn install
- react-native run-android/react-native run-ios
ML
- backend and ML
- pip3 install -r requirements.txt
- python 3 main.py