Virtual Medical Examiner Assessment (VMEA)

Overview

VMEA is an AI-driven medical evaluation system designed for insurance companies to automate health assessments efficiently. It integrates an AI-powered 3D medical avatar, multiple health assessment models, and hospital data to provide structured, real-time evaluations.

Features

• AI-Powered 3D Medical Avatar for virtual assessments
• Multi-Model Health Analysis for accuracy
• Hospital Database Integration for seamless medical data retrieval
• Automated Risk Scoring for underwriting
• Secure & Compliant with industry standards

Tech Stack

Frontend

• Framework: React.js
• 3D Rendering: Three.js (for AI Medical Avatar Visualization)
• Voice Integration: Web Audio API & Speech-to-Text
• Standards: HTML5, CSS3, JavaScript

Backend

• Server Framework: Python (Flask)
• AI/ML Integration: TensorFlow/PyTorch for health models & custom LLMs
• Database: MySQL (for hospital data integration)
• Security: JWT for authentication and secure data transmission

Installation & Setup

Prerequisites

Ensure you have the following installed:

• Python 3
• Node.js & npm
• Virtual Environment for Python (venv recommended)

Backend Setup

1. Clone the repository:

   git clone https://github.com/BlankHead2004/MedSurance.git
   cd MedSurance

2. Install dependencies:

   pip install -r requirements.txt

3. Run the chatbot backend:

   cd Chatbot_backend
   python3 app_with_tts_with_flask.py

   python3 eval2.py

   • This will start the Flask server at http://127.0.0.1:5000

4. Run the hospital management backend:

   cd HospitalManagement_Frontend_Backend/backend
   python3 app.py

   • This will start the hospital API at http://127.0.0.1:5001

Frontend Setup

1. Navigate to the frontend directory:

   cd Final_frontendwithavatar

2. Install dependencies:

   npm i

3. Start the frontend application:

   npm start

   • This will start the frontend, allowing you to interact with the chatbot UI.

Running Hospital Management Frontend

1. Navigate to the frontend folder:

   cd HospitalManagement_Frontend_Backend/frontend

2. Install dependencies:

   npm i

3. Start the frontend:

   npm start

Medical Reports Generated

Patient Data Dashboard

How It Works

• The chatbot backend (app_with_tts_with_flask.py) powers the AI-driven medical assistant.
• The hospital management backend (app.py) handles hospital data and patient records.
• The frontend application provides an interactive UI for virtual health assessments.
• The AI models evaluate health conditions and generate reports for insurance underwriting.