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README.md

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----
-title: MediSync - Multi-Modal Medical Analysis System
-emoji: 🩺
-colorFrom: blue
-colorTo: purple
-sdk: gradio
-sdk_version: "3.41.0"
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
-
-# 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.
-
-Introduction
-MediSync is a multi-modal AI system that combines X-ray image analysis with medical report text processing to provide comprehensive medical insights. By leveraging state-of-the-art deep learning models for both vision and language understanding, MediSync can:
-
-Analyze chest X-ray images to detect abnormalities
-Extract key clinical information from medical reports
-Fuse insights from both modalities for enhanced diagnosis support
-Provide comprehensive visualization of analysis results
-This AI system demonstrates the power of multi-modal fusion in the healthcare domain, where integrating information from multiple sources can lead to more robust and accurate analyses.
-
-System Architecture
-MediSync follows a modular architecture with three main components:
-
-Image Analysis Module: Processes X-ray images using pre-trained vision models
-Text Analysis Module: Analyzes medical reports using NLP models
-Multimodal Fusion Module: Combines insights from both modalities
-The system uses the following high-level workflow:
-
-                      ┌─────────────────┐
-                      │    X-ray Image  │
-                      └────────┬────────┘
-                               │
-                               ▼
-┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
-│  Preprocessing  │───▶│  Image Analysis │───▶│                 │
-└─────────────────┘    └─────────────────┘    │                 │
-                                               │   Multimodal    │
-┌─────────────────┐    ┌─────────────────┐    │     Fusion      │───▶ Results
-│ Medical Report  │───▶│  Text Analysis  │───▶│                 │
-└─────────────────┘    └─────────────────┘    │                 │
-                                               └─────────────────┘
-
-
-## 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 MediSync
-```
-
-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
-
-## Note
-
-This system is designed as a support tool and should not replace professional medical diagnosis. Always consult with healthcare professionals for medical decisions. 
+---
+title: MediSync - Multi-Modal Medical Analysis System
+emoji: 🩺
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 5.20.1
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# 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.
+
+Introduction
+MediSync is a multi-modal AI system that combines X-ray image analysis with medical report text processing to provide comprehensive medical insights. By leveraging state-of-the-art deep learning models for both vision and language understanding, MediSync can:
+
+Analyze chest X-ray images to detect abnormalities
+Extract key clinical information from medical reports
+Fuse insights from both modalities for enhanced diagnosis support
+Provide comprehensive visualization of analysis results
+This AI system demonstrates the power of multi-modal fusion in the healthcare domain, where integrating information from multiple sources can lead to more robust and accurate analyses.
+
+System Architecture
+MediSync follows a modular architecture with three main components:
+
+Image Analysis Module: Processes X-ray images using pre-trained vision models
+Text Analysis Module: Analyzes medical reports using NLP models
+Multimodal Fusion Module: Combines insights from both modalities
+The system uses the following high-level workflow:
+
+                      ┌─────────────────┐
+                      │    X-ray Image  │
+                      └────────┬────────┘
+                               │
+                               ▼
+┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
+│  Preprocessing  │───▶│  Image Analysis │───▶│                 │
+└─────────────────┘    └─────────────────┘    │                 │
+                                               │   Multimodal    │
+┌─────────────────┐    ┌─────────────────┐    │     Fusion      │───▶ Results
+│ Medical Report  │───▶│  Text Analysis  │───▶│                 │
+└─────────────────┘    └─────────────────┘    │                 │
+                                               └─────────────────┘
+
+
+## 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 MediSync
+```
+
+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
+
+## Note
+
+This system is designed as a support tool and should not replace professional medical diagnosis. Always consult with healthcare professionals for medical decisions.