Vega AI – Medical Report Analysis Platform

Overview

Vega AI is a healthcare-focused AI platform designed to assist patients and healthcare professionals by generating structured medical reports from uploaded medical documents and images.

The platform enables users to:

• Upload medical reports, scans, and diagnostic documents.
• Generate AI-assisted clinical observations.
• Store and manage generated reports.
• Validate reports through expert review workflows.
• Maintain a structured audit trail of report activities.
• Integrate with Firebase for authentication and cloud services.

Disclaimer: Vega AI provides AI-generated insights intended to support healthcare professionals. It is not a substitute for professional medical diagnosis, treatment, or clinical judgment.

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Features

AI Report Generation

• Medical document analysis
• Structured clinical observations
• Confidence-based findings
• Patient-specific report generation

Report Management

• Report history tracking
• Timestamped audit trail
• Status management
• Validation workflow

Clinical Review Workflow

• AI Generated
• Expert Reviewed
• Clinically Validated

Firebase Integration

• Authentication support
• Cloud configuration support
• Secure environment variable management

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Project Structure

vega-ai/
│
├── frontend/
│   └── index.html
│
├── data/
│   └── reports.json
│
├── server.py
├── requirements.txt
├── .gitignore
└── README.md

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Technology Stack

Backend

• Python 3
• ThreadingHTTPServer
• REST API Architecture

Frontend

• HTML
• CSS
• JavaScript

Database

• JSON-based storage (Demo)
• Firebase Integration Support

Cloud Deployment

• Render

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API Endpoints

Health Check

GET /api/health

Response:

{
  "ok": true,
  "service": "Vega Medical AI"
}

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Firebase Configuration

GET /api/firebase-config

Returns public Firebase configuration values.

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Get Reports

GET /api/reports

Returns all generated reports.

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Analyze Medical Document

POST /api/analyze

Accepts:

• Multipart form uploads
• JSON requests

Generates a structured medical report.

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Validate Report

POST /api/reports/{report_id}/validate

Validation states:

• ai_generated
• expert_reviewed
• clinically_validated

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Local Installation

Clone Repository

git clone https://github.com/shrikargs7-cloud/vega-ai.git
cd vega-ai

Create Virtual Environment

python -m venv venv

Activate Environment

macOS/Linux:

source venv/bin/activate

Windows:

venv\Scripts\activate

Install Dependencies

pip install -r requirements.txt

Run Application

python server.py

Application will be available at:

http://localhost:8000

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Environment Variables

Create a .env file:

FIREBASE_API_KEY=
FIREBASE_AUTH_DOMAIN=
FIREBASE_PROJECT_ID=
FIREBASE_STORAGE_BUCKET=
FIREBASE_MESSAGING_SENDER_ID=
FIREBASE_APP_ID=

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Deployment on Render

Build Command

pip install -r requirements.txt

Start Command

python server.py

Required Render Environment Variables

FIREBASE_API_KEY
FIREBASE_AUTH_DOMAIN
FIREBASE_PROJECT_ID
FIREBASE_STORAGE_BUCKET
FIREBASE_MESSAGING_SENDER_ID
FIREBASE_APP_ID

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Future Roadmap

• OpenAI GPT Integration
• Gemini API Integration
• Medical Image Analysis
• DICOM Support
• Doctor Dashboard
• Patient Portal
• Cloud Database Storage
• Multi-user Authentication
• HIPAA-Oriented Security Enhancements
• AI-Assisted Clinical Decision Support

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Disclaimer

Vega AI is an educational and research-oriented healthcare technology project. All AI-generated outputs must be reviewed by qualified healthcare professionals before clinical use. The developers assume no responsibility for medical decisions made using generated reports.

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Author

Shrikar G

AI Developer | Full-Stack Developer | Healthcare AI Enthusiast

GitHub: https://github.com/shrikargs7-cloud