---
title: Medical Report Analysis Platform
emoji: 🏥
colorFrom: blue
colorTo: purple
sdk: docker
pinned: false
license: mit
app_port: 7860
---

# Medical Report Analysis Platform

Advanced AI-powered medical document analysis using 50+ specialized models across 9 clinical domains.

## 🚀 Features

### Two-Layer AI Architecture
- **Layer 1**: PDF extraction, document classification, and intelligent routing
- **Layer 2**: Specialized model analysis with concurrent processing

### 50+ Specialized Medical Models
- Clinical Notes (MedGemma 27B, Bio_ClinicalBERT)
- Radiology (MedGemma 4B Multimodal, MONAI)
- Pathology (Path Foundation, UNI2-h)
- Cardiology (HuBERT-ECG)
- Laboratory (DrLlama, Lab-AI)
- Drug Interactions (CatBoost DDI)
- Diagnosis & Triage (MedGemma 27B)
- Medical Coding (Rayyan Med Coding)
- Mental Health (MentalBERT)

### Comprehensive Analysis
- Multi-modal content extraction (text, images, tables)
- Document type classification
- Specialized model routing
- Concurrent processing
- Result synthesis and validation
- Clinical insights generation

### Regulatory Compliance
- HIPAA compliant architecture
- GDPR aligned data processing
- FDA guidance adherence
- Medical-grade security

## 📖 Usage

1. **Upload**: Drag and drop or select a medical PDF report
2. **Process**: Wait 30-60 seconds for comprehensive AI analysis
3. **Review**: Explore detailed results, insights, and recommendations

## ⚠️ Important Disclaimer

This platform provides AI-assisted analysis and is designed for clinical decision support. 

**All results must be reviewed and verified by qualified healthcare professionals.**

- Not a substitute for professional medical judgment
- Requires specialist review for clinical decisions
- Performance varies by document quality and type
- Intended for research and development purposes

## 🔒 Security & Privacy

- Encrypted data transmission
- Temporary file processing (no persistent storage)
- Secure handling of medical information
- Compliance with healthcare data protection standards

## 🛠️ Technical Details

### Architecture
- **Backend**: FastAPI + Python
- **Frontend**: React + TypeScript + TailwindCSS
- **AI Models**: 50+ Hugging Face models
- **Processing**: Multi-modal PDF analysis with OCR

### Performance
- Layer 1 Processing: < 2 seconds per page
- Document Classification: < 500 ms
- Specialized Analysis: 2-10 seconds
- Total Analysis Time: 30-60 seconds

## 📚 Documentation

Comprehensive documentation available in the repository:
- Architecture Design
- Pipeline Design
- Model Mapping
- Compliance Guidelines

## 🤝 Support

For issues, questions, or feedback:
- Review the documentation
- Check the logs for detailed error messages
- Report issues through the Space discussions

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**Medical Report Analysis Platform** - Advanced AI-Powered Clinical Intelligence

Built with comprehensive research following FDA guidance, HIPAA requirements, GDPR principles, and medical AI best practices.