SpecializedMD - Medical Education Platform

A comprehensive medical education platform focused on colorectal surgery techniques, combining multimedia content, expert annotations, and AI-powered learning assistance.

Project Overview

SpecializedMD is designed to create an enriched learning environment by:

• Managing multimedia content (video, audio, transcripts)
• Supporting professor annotations and cut-away explanations
• Integrating external medical literature and research
• Generating synthetic Q&A data for enhanced learning
• Providing an AI-powered question answering system

Project Structure

SpecializedMD/
├── api/                    # Backend API endpoints
├── assets/                # Project assets and media
├── core/                  # Core business logic
│   ├── content/          # Content management
│   ├── annotation/       # Annotation processing
│   ├── settings/         # Application settings
│   ├── rag/             # Retrieval-augmented generation
│   └── qa/              # Question-Answer generation
├── data/                 # Data storage
│   ├── lectures/         # Raw lecture content
│   ├── annotations/      # Professor annotations
│   └── external/         # External literature
├── models/               # AI model implementations
├── services/            # External service integrations
├── web/                 # Web interface
└── utils/               # Utility functions

Features

1. Content Management

   • Video/audio lecture storage
   • Transcript generation and management
   • Annotation system for professor insights

2. Knowledge Integration

   • External medical literature integration
   • Case study management
   • Reference linking system

3. AI-Powered Learning

   • Question-Answer generation
   • Context-aware search
   • Learning path recommendations

4. Interactive Platform

   • Real-time annotation tools
   • Student feedback system
   • Settings management with secure API key storage

Configuration

The platform uses a secure settings management system for handling API keys and configuration:

• API keys are stored securely in the user's home directory
• Automatic backup creation before settings changes
• User-friendly configuration UI
• Support for multiple external services:
  • PubMed/NCBI API for medical literature
  • AWS S3 for content storage
  • Groq and DeepSeek for AI models
  • UMLS for medical terminology

Getting Started

1. Clone the repository
2. Install dependencies:

   pip install -r requirements.txt

3. Configure API keys using the settings UI:

   from core.settings import show_settings
   show_settings()