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
.savfiles - 🎛️ 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
- 🔷 Get Diagnosed
# Clone the repository
git clone https://github.com/Ashis-Mishra07/Medical_Diagnose.git
cd Medical_Diagnose
# 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.txtThe app will open at http://localhost:8501
Multiple_Disease_Prediction_Model/
├── app.py # Main Streamlit web application
├── requirements.txt # List of all required Python libraries
├── models/ # Directory containing trained models
│ ├── diabetes_model.sav # Machine Learning model (Pickle format)
│ ├── heart_disease_model.sav # Machine Learning model (Pickle format)
│ ├── parkinsons_model.sav # Machine Learning model (Pickle format)
│ ├── breast_cancer_model.keras # Deep Learning model (TensorFlow Keras format)
│ └── diagnosis_model.sav # Additional ML model for general diagnosis
└── README.md # Project documentation (you’re reading it!)
An enhanced machine learning-powered module that not only predicts the disease but also provides a comprehensive health recommendation package.
-
🦠 Disease
Get a prediction of the most probable disease based on your inputs. -
📖 Description
A clear and concise explanation of the diagnosed condition. -
🛡️ Precaution
Proactive steps to reduce risk or manage the condition effectively. -
💊 Medication
A list of commonly prescribed medicines for reference (not for self-medication). -
🏃 Workout
Recommended physical activities and fitness routines that support your condition. -
🥗 Diets
Nutrition advice and diet plans to assist in managing or preventing the disease.
This feature aims to bridge prediction with actionable lifestyle insights, helping users make informed, health-conscious decisions post-diagnosis.
After receiving your diagnosis, interact with our AI-powered Health Chatbot to better understand your condition, clarify doubts, and explore additional wellness tips.
-
🧠 Conversational Support
Ask questions like “What is this disease?”, “How serious is it?”, or “How can I avoid it?” — and receive human-like responses powered by advanced AI models. -
🩺 Follow-up Guidance
The chatbot can summarize your diagnosis and suggest follow-up actions, including questions to ask your real doctor. -
🔗 Instant Relevance
It uses your diagnosis data to personalize the interaction — no need to repeat your inputs. -
🧭 User-Friendly Interface
Smooth, interactive, and beginner-friendly — even non-technical users can easily navigate it.
🗨️ This feature makes your health journey easier and more engaging, offering a virtual companion right after your results are presented.
- 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