A machine learning-powered web application built with Streamlit to predict the presence of common diseases including Diabetes, Heart Disease, Parkinson’s, and Breast Cancer. Users can enter basic health metrics and receive immediate predictions.
This project aims to provide a simple yet effective tool for early disease prediction. It features:
- ✅ Trained ML models saved as
.sav
files - 🎛️ Interactive web interface using Streamlit
- 📦 Easy-to-install Python environment
- 🔍 Real-time disease prediction
The following diseases are currently supported:
- 🔷 Diabetes
- 🔴 Heart Disease
- 🟠 Parkinson’s Disease
- 🟢 Breast Cancer
# Clone the repository
git clone https://github.com/Ashis-Mishra07/Multiple_Disease_Prediction_Model.git
cd Multiple_Disease_Prediction_Model
# Create a virtual environment (optional but recommended)
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install required packages
pip install -r requirements.txt
The app will open at http://localhost:8501
Multiple_Disease_Prediction_Model/
├── app.py # Main Streamlit web app
├── requirements.txt # Python dependencies
├── models/ # Trained model files (.sav)
│ ├── diabetes_model.sav
│ ├── heart_disease_model.sav
│ ├── parkinsons_model.sav
│ └── breast_cancer_model.sav
└── README.md # You're reading it!
- Add model accuracy indicators
- Add model retraining support from UI
- Integrate user authentication
- Integration with EEG devices
- Deploy on Streamlit Cloud or HuggingFace Spaces
📅 Last Updated: June 2025 | 🔢 Version: 1.0.0