| | --- |
| | title: U-HRES - Unified Health Record Exchange System AI Layer |
| | emoji: 🤖 |
| | colorFrom: blue |
| | colorTo: purple |
| | sdk: gradio |
| | sdk_version: 5.20.1 |
| | app_file: run.py |
| | pinned: false |
| | --- |
| | |
| | # U-HRES: Unified Health Record Exchange System AI Layer |
| |
|
| | U-HRES 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 |
| |
|
| | 1. Clone this repository: |
| | ```bash |
| | git clone [repository-url] |
| | cd Multi-Modal-Medical-Analysis-System |
| | ``` |
| |
|
| | 2. Install dependencies: |
| | ```bash |
| | pip install -r requirements.txt |
| | ``` |
| |
|
| | 3. Run the application: |
| | ```bash |
| | python app.py |
| | ``` |
| |
|
| | 4. 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 |
| |
|
| | ## Environment Variables |
| |
|
| | - **HF_TOKEN** (optional): Hugging Face token for accessing private models or improved rate limits. If not set, the system will use public models without authentication. |
| | |
| | ## Note |
| | |
| | This system is designed as a support tool and should not replace professional medical diagnosis. Always consult with healthcare professionals for medical decisions. |
