Medical Recommendation System

The Medical Recommendation System is an intelligent healthcare assistant designed to provide personalized medical guidance based on user symptoms. Using Machine Learning (Random Forest Regressor), it predicts suitable medicines, offers dietary recommendations, and provides a nearby hospital locator, ensuring quick access to medical assistance.

🏥 Features

• Symptom-Based Medicine Recommendation: Predicts the most suitable medicines using Machine Learning.
• Dietary Suggestions: Recommends diet plans to aid recovery and overall health.
• Nearby Hospital Locator: Helps users find healthcare facilities based on their location.
• User-Friendly Interface: Built with Flask, making it accessible even for non-technical users.
• Holistic Healthcare Approach: Empowers users with quick, data-driven medical advice.
• Decision-Support for Professionals: Can assist healthcare professionals in preliminary diagnoses.

🚀 Tech Stack

• Backend: Flask (Python)
• Machine Learning: Scikit-learn (Random Forest Regressor)
• Frontend: HTML, CSS, JavaScript
• APIs: Google Maps API (for hospital locator)
• Database (Optional): CSV/JSON-based storage for symptom-disease mapping

📂 Project Structure

Medical-Recommendation-System/
│── static/           # CSS, JS, images
│── templates/        # HTML templates
│── models/           # Machine learning models
│── app.py            # Main Flask application
│── requirements.txt  # Dependencies
│── README.md         # Project documentation

⚙️ Installation & Setup

Prerequisites

• Python 3.x installed
• Flask & required dependencies

Steps to Run the Project

1. Clone the repository

   git clone https://github.com/your-username/Medical-Recommendation-System.git
   cd Medical-Recommendation-System

2. Create a virtual environment (Optional but recommended)

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

   pip install -r requirements.txt

4. Run the Flask application

   python app.py

5. Access the application Open your browser and go to: http://127.0.0.1:5000/

🧠 How It Works

1. User Inputs Symptoms: The system takes user symptoms as input.
2. Machine Learning Model Processes Data: The Random Forest Regressor model predicts potential medicines.
3. Dietary Suggestions Provided: The system recommends foods to aid in recovery.
4. Hospital Locator Activated: Based on the user’s location, nearby hospitals are displayed.

🎯 Use Cases

• Self-Assessment: Get quick insights before consulting a doctor.
• Remote & Rural Areas: Useful where healthcare access is limited.
• Medical Decision Support: Helps doctors streamline diagnosis.

🌍 Impact & Benefits

✔️ Reduces dependency on immediate doctor consultations for minor concerns ✔️ Aids in early disease detection and management ✔️ Bridges the gap between technology and healthcare ✔️ Cost-effective and accessible healthcare solution

📜 License

This project is licensed under the MIT License.

🤝 Contributing

Contributions are welcome! Feel free to fork the repository and submit a pull request.

📬 Contact

If you have any questions or suggestions, feel free to reach out:

• Email: [email protected]
• GitHub: Suke2004
• LinkedIn: Sukesh Reddy Ustela

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🚀 Empowering healthcare with technology!