hardikagarwal26 / medichoice

MEDICHOICE is a machine learning app that predicts diseases from input data and recommends Ayurvedic medicines. It combines modern data science with traditional Ayurvedic knowledge to offer personalized healthcare solutions through an intuitive interface.

MEDICHOICE

Project Overview

MEDICHOICE is a machine learning-based application designed to predict diseases based on input data and recommend appropriate Ayurvedic medicines for the diagnosed conditions. This project aims to leverage the power of data science and traditional Ayurvedic knowledge to provide an integrative approach to healthcare.

Features

• Disease Prediction: Utilizes a dataset to train models that can predict potential diseases based on given input parameters.
• Ayurvedic Medicine Recommendation: Provides recommendations for Ayurvedic treatments tailored to the predicted diseases.
• User-Friendly Interface: Easy-to-use interface for data input and result visualization.

Usage

1. Data Preprocessing:

   • Use the data_preprocessing.py script or the data_preprocessing.ipynb notebook to preprocess the dataset. bash python src/data_preprocessing.py

2. Train the Model:

   • Train the disease prediction model using the train_model.py script or the model_training.ipynb notebook. bash python src/train_model.py

3. Run the Application:

   • Start the Flask web application to input patient data and get predictions. bash python app/app.py

   • Open a web browser and navigate to http://127.0.0.1:5000 to use the application.

Acknowledgments

• Thanks to the open-source community for their valuable resources and tools.
• Special thanks to the contributors who have helped improve this project.