Live Healthy App

This repository hosts a Python desktop application designed to assist in medical diagnostics and streamline doctor-patient interactions. The app leverages AI technology (ResNet) to analyze X-ray scans and integrates several features for patients, doctors, and radiologists.

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Features

For Patients

• AI-Powered X-Ray Scan Predictions
  Upload your X-ray scan, and the system will predict potential medical conditions for respiratory diseases using a ResNet AI model.

• Doctor Chat System
  Connect with certified doctors for personalized medical advice.

• VIP Membership Benefits

  • Purchase coins to upgrade your VIP level.
  • Enjoy discounts on system features, including doctor consultations and advanced AI predictions.

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For Doctors

• Consultation and Earnings
  • Engage in chats with patients.
  • Earn coins for every consultation, which can be redeemed for other system benefits.

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For Radiologists

• Batch X-Ray Analysis
  • Predict results for individual X-ray scans or process entire folders containing multiple scans.
  • Enhance efficiency with the AI model's high-accuracy predictions.

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Installation

Step 1: Clone the Repository

Step 2: Install Dependencies Ensure Python 3.8+ is installed Step 3: Run the Application

python starter.py

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Tech Stack

Backend AI Model: ResNet for X-ray image prediction.

Language: Python.

GUI Framework: Tkinter.

Database: MYSQL.

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Usage Guide

For Patients

1. Create an account or log in.

2. Upload your X-ray scan for analysis or start a chat with a doctor.

3. Purchase coins to unlock VIP features or discounted services.

For Doctors

1. Log in to the system.

2. Respond to patient queries and earn coins.

For Radiologists

1. Access the "Batch Analysis" feature.

2. Upload a folder containing multiple scans for batch predictions.

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Future Enhancements

Integration with Electronic Health Records (EHR) systems.

Support for more advanced AI models.

Enhanced chat features, including video consultations.

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Contributing

We welcome contributions! To contribute:

1. Fork the repository.

2. Create a branch for your feature or bugfix.

3. Submit a pull request with detailed changes.

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License

This project is licensed under the MIT License. See the LICENSE file for more information.