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This project is a Flask-based platform for patients, donors, and doctors, integrating hospital management in one solution. It uses Machine Learning models for predictive health analysis and Power BI for interactive dashboards. Through this project, I enhanced my skills in full-stack development, applied ML, and healthcare data solutions.

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jahanOSTG/Healthguard_With-Smart-AI-Diagnosis-Hub

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Luvia Health Center with AI Powered

Overview

This project is a Flask-based platform for patients, donors, and doctors, integrating hospital management into a unified solution.
It leverages Machine Learning models for predictive health analysis (diabetes, cancer, pregnancy) and Power BI dashboards for interactive data visualization.


Features

Patient Management

  • Register, view, and update patient information
  • Book appointments and track medical history

Doctor Management

  • Admins can manage doctor profiles and schedules
  • Doctors can view assigned patients and appointments

Donor Management

  • Register donors and match with patient needs

Machine Learning Integration

  • Predictive health analysis for diabetes, cancer, and pregnancy
  • Provides actionable insights for patients and doctors

Power BI Integration

  • Interactive dashboards for hospital data visualization
  • Real-time reporting for admins and management

User Roles

  • Role-based access for patients, doctors, donors, and admin

Tech Stack

  • Backend: Python, Flask
  • Frontend: HTML5, CSS3, JavaScript
  • Database: SQLite, MySQL
  • Machine Learning: scikit-learn, Pandas, NumPy
  • Data Visualization: Power BI

Quick Start

  1. Download the source code from the repository.
  2. Install dependencies using pip:
pip install flask

3.Run the application

python app.py

4.Open in browser:

Navigate to

http://127.0.0.1:5000/

to access the platform.

License

This project is licensed under the MIT License.

About

This project is a Flask-based platform for patients, donors, and doctors, integrating hospital management in one solution. It uses Machine Learning models for predictive health analysis and Power BI for interactive dashboards. Through this project, I enhanced my skills in full-stack development, applied ML, and healthcare data solutions.

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