Sympto-Tracker is a web application that allows users to track their symptoms and predict the likelihood of developing certain diseases. The application is built using React, Flask, and RStudio, and currently supports the prediction of the following diseases:
Liver CirrhosisMesotheliomaChronic Kidney DiseaseCoronary Heart DiseaseDiabetes Mellitus
For predicting the disease diagnosis we used Supervised Binary Classification Machine Learning models, and used the following algorithms:
Logistic RegressionSupport Vector MachineXGBoost
| Name | Use Case | |
|---|---|---|
 |
React.js | Frontend Web Framework |
 |
Node.js | Runtime Environment |
 |
Flask | Backend Web Framework |
 |
Python | Machine Learning Models |
 |
R | Data Analysis and Visualization |
To run the application, you will need to have Node.js, Python, and R installed on your computer.
-
Clone the repository:
git clone https://github.com/harshitv804/sympto-tracker.git -
Install the dependencies for the frontend and backend:
cd sympto-tracker/frontend npm installcd ../backend pip install -r requirements.txt -
Start the frontend and backend servers:
cd sympto-tracker/frontend npm startcd ../backend python app.py -
Navigate to
http://localhost:3000in your web browser to use the application.
To use Sympto-Tracker, simply enter your symptoms into the form on the home page and click Predict. The application will use machine learning algorithms to predict the likelihood of developing each of the supported diseases based on your symptoms.
Sympto-Tracker was developed by:
| Name | Profile Link | |
|---|---|---|
 |
Harshit V | https://github.com/harshitv804 |
 |
Anto Vimalan | https://github.com/vimalds15 |
 |
Prawin RP | https://github.com/PRAWIN392 |
 |
Aniket Kumar | https://github.com/ak736 |
If you have any questions or feedback, please reach out to [harshitv804@gmail.com]
This project is licensed under the MIT License. See the LICENSE file for details.