Shushruta: Disease Prediction System

Overview

Shushruta is a comprehensive tool designed to predict multiple diseases, including diabetes, heart disease, and Parkinson's disease, using machine learning models. The system leverages various datasets and provides a user-friendly interface for making predictions.

Features

• Multi-Disease Prediction: Supports predictions for diabetes, heart disease, and Parkinson's disease.
• Machine Learning Models: Utilizes advanced machine learning techniques for accurate predictions.
• User-Friendly Interface: Easy-to-use interface built with Streamlit for seamless interaction.
• Extensive Datasets: Uses well-known datasets to train and validate models.

Project Structure

Shushruta-main/
├── dataset/
│   ├── diabetes.csv
│   ├── heart.csv
│   └── parkinsons.csv
├── notebooks/
│   ├── Multiple disease prediction system - diabetes.ipynb
│   ├── Multiple disease prediction system - heart.ipynb
│   └── Multiple disease prediction system - Parkinsons.ipynb
|── models/
|   ├── diabetes_model.sav
|   ├── heart_disease_model.sav
|   └── parkinsons_model.sav
├── requirements.txt
└── streamlit_app.py

Installation

Prerequisites

• Python 3.10 or Above
• Streamlit

Steps

1. Clone the Repository

   git clone https://github.com/abhinababiswas01/Shushruta.git
   cd Shushruta

2. Install Dependencies

   pip install -r requirements.txt

3. Run the Streamlit Application

   streamlit run streamlit_app.py

Usage

1. Open your browser and navigate to the Streamlit app (usually at http://localhost:8501).
2. Select the disease you want to predict (diabetes, heart disease, or Parkinson's).
3. Enter the required input parameters.
4. Click on the "Predict" button to get the prediction results.

Datasets

• Diabetes Dataset: Contains various health metrics used to predict diabetes.
• Heart Disease Dataset: Includes features relevant to heart disease prediction.
• Parkinson's Disease Dataset: Consists of attributes related to Parkinson's disease.

Notebooks

The project includes Jupyter notebooks for each disease prediction model, detailing the data preprocessing, model training, and evaluation processes:

• Multiple disease prediction system - diabetes.ipynb
• Multiple disease prediction system - heart.ipynb
• Multiple disease prediction system - Parkinsons.ipynb

Contributing

We welcome contributions from the community! Please read our contributing guidelines before making any changes.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For any questions or suggestions, please reach out to us at abhinababiswas0001@gmail.com.