title: Medical Analysis System emoji: 🤖 colorFrom: blue colorTo: purple sdk: gradio sdk_version: 5.20.1 app_file: app.py pinned: false
MediSync: Multi-Modal Medical Analysis System
MediSync is an AI-powered healthcare solution that combines X-ray image analysis with patient report text processing to provide comprehensive medical insights.
Features
- X-ray Image Analysis: Detects abnormalities in chest X-rays using pre-trained vision models from Hugging Face.
- Medical Report Processing: Extracts key information from patient reports using NLP models.
- Multi-modal Integration: Combines insights from both image and text data for more accurate diagnosis suggestions.
- User-friendly Interface: Simple web interface for uploading images and reports.
Project Structure
mediSync/
├── app.py # Main application with Gradio interface
├── models/
│ ├── image_analyzer.py # X-ray image analysis module
│ ├── text_analyzer.py # Medical report text analysis module
│ └── multimodal_fusion.py # Fusion of image and text insights
├── utils/
│ ├── preprocessing.py # Data preprocessing utilities
│ └── visualization.py # Result visualization utilities
├── data/
│ └── sample/ # Sample data for testing
└── tests/ # Unit tests
Setup Instructions
- Clone this repository:
git clone [repository-url]
cd MediSync
- Install dependencies:
pip install -r requirements.txt
- Run the application:
python app.py
- Access the web interface at
http://localhost:7860
Models Used
- X-ray Analysis: facebook/deit-base-patch16-224-medical-cxr
- Medical Text Analysis: medicalai/ClinicalBERT
- Additional Support Models: Medical question answering and entity recognition models
Use Cases
- Preliminary screening of chest X-rays
- Cross-validation of radiologist reports
- Educational tool for medical students
- Research tool for studying correlation between visual findings and written reports
Note
This system is designed as a support tool and should not replace professional medical diagnosis. Always consult with healthcare professionals for medical decisions.