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Our project integrates blood donation management with ML-based disease prediction. Donors not only contribute blood but also receive a health report indicating potential diseases. Built with Express.js, MongoDB, and Python, this system ensures a user-friendly and secure experience. Contributions welcome!

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Blood Donation System with ML Disease Prediction

Welcome to our Blood Donation System with Machine Learning Disease Prediction!

Introduction

Our system not only facilitates blood donation but also provides valuable insights into potential health risks using machine learning algorithms. By donating blood, users can receive a comprehensive report indicating possible diseases they may be predisposed to.

Features

  • Blood Donation Management: Easily register for blood donation and manage donation appointments.
  • Disease Prediction: Utilize machine learning models to predict potential health conditions based on user data.
  • Personalized Health Reports: Receive detailed reports outlining potential diseases and health recommendations.
  • User Profile Management: Maintain personal profiles and track donation history.

Technologies Used

  • Python: For machine learning algorithms.
  • Express JS
  • Tensor Flow
  • HTML/CSS/JavaScript: Frontend development for user interaction.
  • MongoDB: Database management for storing user data.

Installation

  1. Clone the repository:
    git clone https://github.com/your-username/blood-donation-ML-system.git
  2. Install dependencies:
    pip install -r requirements.txt
  3. Run the application:
    python app.py
  4. Access the application through your web browser at http://localhost:5000.

Contributers

1.Mahavir Sancheti (Mahavir2112)

2.Prateek Pathak (prateek2pathak)

3.Buddhisagar Panjiyar (iam-buddhi)

4.Yuvraj Siangh (yuvrajSingh930)

5.Manoj Palakki (croocyrepo1462)

6.Garv Sethia

About

Our project integrates blood donation management with ML-based disease prediction. Donors not only contribute blood but also receive a health report indicating potential diseases. Built with Express.js, MongoDB, and Python, this system ensures a user-friendly and secure experience. Contributions welcome!

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