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An AI-powered disease prediction system using machine learning and a chatbot assistant built with Gemini API for health-related queries.

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🧬 Disease Prediction Web Application

👨‍💻 Developed by:

Shinjan Saha, Satyabrata Das Adhikari and Abesh Chakraborty


🧠 Project Overview

This web-based health assistant predicts the likelihood of multiple diseases—Breast Cancer, Brain Tumor, Pneumonia, Diabetes, and Heart Disease—based on user input. Built using Flask, Machine Learning, and enhanced with a Gemini-powered AI chatbot, this system offers quick and interactive diagnostics support.


🙌 Contribution Highlights

  • Shinjan Saha

    • Built and trained model for heart disease detection
    • Integrated all trained ML models into the Flask backend
    • Created interactive and user-friendly forms for tabular predictions
    • Integrated Gemini API to add a smart chatbot assistant
  • Fellow team members

    • Built and trained models for diabetes, breast cancer, pneumonia, and brain tumor detection
    • Preprocessed datasets and saved model pipelines using joblib
    • Supported UI testing and feedback integration

💻 Features

  • 🔍 Predicts 5 diseases from medical data or uploaded images
  • 📊 Tabular form inputs with sliders, dropdowns, and radio buttons
  • 🧠 Gemini chatbot for symptom-based health conversations
  • 💾 Model files saved using joblib for seamless deployment
  • 💡 Clean, responsive design with modern UI/UX

⚙️ Tech Stack

  • Backend: Flask
  • Frontend: HTML5, CSS3 (Jinja2 Templating)
  • ML Tools: scikit-learn, joblib, pandas, TensorFlow
  • Chatbot: Gemini API (Google Generative AI)
  • Deployment Ready: GitHub integrated

🚀 How to Run
Clone the repo:

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git clone https://github.com/Code-r4Life/Disease-prediction-app.git
Navigate to the project folder:

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cd disease-prediction-app
(Optional) Create a virtual environment

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python -m venv venv
source venv/bin/activate   # For Linux/Mac
.\venv\Scripts\activate    # For Windows
Install dependencies:

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pip install -r requirements.txt
Add your .env file containing the Gemini API key:

ini
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GEMINI_API_KEY=your_key_here
Run the app:

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python app.py

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An AI-powered disease prediction system using machine learning and a chatbot assistant built with Gemini API for health-related queries.

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