https://github.com/abhinaba-biswas/shushruta
Healthcare assistant able to detect : Heart Disease, Parkinson's disease, Diabetes
https://github.com/abhinaba-biswas/shushruta
disease-prediction machine-learning streamlit streamlit-webapp
Last synced: 7 months ago
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Healthcare assistant able to detect : Heart Disease, Parkinson's disease, Diabetes
- Host: GitHub
- URL: https://github.com/abhinaba-biswas/shushruta
- Owner: abhinaba-biswas
- License: mit
- Created: 2024-08-26T11:37:14.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-09-21T04:31:54.000Z (about 1 year ago)
- Last Synced: 2025-02-07T00:18:01.660Z (8 months ago)
- Topics: disease-prediction, machine-learning, streamlit, streamlit-webapp
- Language: Jupyter Notebook
- Homepage: https://shushruta.onrender.com/
- Size: 89.8 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 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](https://www.python.org/)
- [Streamlit](https://streamlit.io/)
### Steps
1. **Clone the Repository**
```bash
git clone https://github.com/abhinababiswas01/Shushruta.git
cd Shushruta
```
2. **Install Dependencies**
```bash
pip install -r requirements.txt
```
3. **Run the Streamlit Application**
```bash
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](CONTRIBUTING.md) before making any changes.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Contact
For any questions or suggestions, please reach out to us at [abhinababiswas0001@gmail.com](mailto:abhinababiswas0001@gmail.com).
