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- # MediSync: Multi-Modal Medical Analysis System
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-
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- MediSync is an AI-powered healthcare solution that combines X-ray image analysis with patient report text processing to provide comprehensive medical insights.
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-
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- ## Features
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-
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- - **X-ray Image Analysis**: Detects abnormalities in chest X-rays using pre-trained vision models from Hugging Face.
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- - **Medical Report Processing**: Extracts key information from patient reports using NLP models.
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- - **Multi-modal Integration**: Combines insights from both image and text data for more accurate diagnosis suggestions.
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- - **User-friendly Interface**: Simple web interface for uploading images and reports.
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-
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- ## Project Structure
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-
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- ```
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- mediSync/
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- β”œβ”€β”€ app.py # Main application with Gradio interface
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- β”œβ”€β”€ models/
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- β”‚ β”œβ”€β”€ image_analyzer.py # X-ray image analysis module
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- β”‚ β”œβ”€β”€ text_analyzer.py # Medical report text analysis module
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- β”‚ └── multimodal_fusion.py # Fusion of image and text insights
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- β”œβ”€β”€ utils/
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- β”‚ β”œβ”€β”€ preprocessing.py # Data preprocessing utilities
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- β”‚ └── visualization.py # Result visualization utilities
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- β”œβ”€β”€ data/
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- β”‚ └── sample/ # Sample data for testing
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- └── tests/ # Unit tests
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- ```
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-
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- ## Setup Instructions
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-
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- 1. Clone this repository:
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- ```bash
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- git clone [repository-url]
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- cd MediSync
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- ```
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-
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- 2. Install dependencies:
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- ```bash
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- pip install -r requirements.txt
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- ```
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-
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- 3. Run the application:
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- ```bash
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- python app.py
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- ```
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-
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- 4. Access the web interface at `http://localhost:7860`
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-
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- ## Models Used
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-
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- - **X-ray Analysis**: facebook/deit-base-patch16-224-medical-cxr
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- - **Medical Text Analysis**: medicalai/ClinicalBERT
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- - **Additional Support Models**: Medical question answering and entity recognition models
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-
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- ## Use Cases
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-
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- - Preliminary screening of chest X-rays
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- - Cross-validation of radiologist reports
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- - Educational tool for medical students
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- - Research tool for studying correlation between visual findings and written reports
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-
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- ## Note
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-
 
 
 
 
 
 
 
 
 
 
 
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  This system is designed as a support tool and should not replace professional medical diagnosis. Always consult with healthcare professionals for medical decisions.
 
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+ ---
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+ title: MediSync - Multi-Modal Medical Analysis System
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+ emoji: 🩺
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+ colorFrom: blue
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+ colorTo: yellow
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+ sdk: gradio
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+ sdk_version: "3.41.0"
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+ app_file: app.py
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+ pinned: false
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+ ---
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+
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+ # MediSync: Multi-Modal Medical Analysis System
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+
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+ MediSync is an AI-powered healthcare solution that combines X-ray image analysis with patient report text processing to provide comprehensive medical insights.
15
+
16
+ ## Features
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+
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+ - **X-ray Image Analysis**: Detects abnormalities in chest X-rays using pre-trained vision models from Hugging Face.
19
+ - **Medical Report Processing**: Extracts key information from patient reports using NLP models.
20
+ - **Multi-modal Integration**: Combines insights from both image and text data for more accurate diagnosis suggestions.
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+ - **User-friendly Interface**: Simple web interface for uploading images and reports.
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+
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+ ## Project Structure
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+
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+ ```
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+ mediSync/
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+ β”œβ”€β”€ app.py # Main application with Gradio interface
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+ β”œβ”€β”€ models/
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+ β”‚ β”œβ”€β”€ image_analyzer.py # X-ray image analysis module
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+ β”‚ β”œβ”€β”€ text_analyzer.py # Medical report text analysis module
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+ β”‚ └── multimodal_fusion.py # Fusion of image and text insights
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+ β”œβ”€β”€ utils/
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+ β”‚ β”œβ”€β”€ preprocessing.py # Data preprocessing utilities
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+ β”‚ └── visualization.py # Result visualization utilities
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+ β”œβ”€β”€ data/
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+ β”‚ └── sample/ # Sample data for testing
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+ └── tests/ # Unit tests
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+ ```
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+
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+ ## Setup Instructions
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+
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+ 1. Clone this repository:
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+ ```bash
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+ git clone [repository-url]
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+ cd MediSync
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+ ```
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+
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+ 2. Install dependencies:
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+ ```bash
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+ pip install -r requirements.txt
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+ ```
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+
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+ 3. Run the application:
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+ ```bash
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+ python app.py
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+ ```
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+
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+ 4. Access the web interface at `http://localhost:7860`
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+
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+ ## Models Used
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+
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+ - **X-ray Analysis**: facebook/deit-base-patch16-224-medical-cxr
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+ - **Medical Text Analysis**: medicalai/ClinicalBERT
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+ - **Additional Support Models**: Medical question answering and entity recognition models
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+
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+ ## Use Cases
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+
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+ - Preliminary screening of chest X-rays
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+ - Cross-validation of radiologist reports
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+ - Educational tool for medical students
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+ - Research tool for studying correlation between visual findings and written reports
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+
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+ ## Note
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+
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  This system is designed as a support tool and should not replace professional medical diagnosis. Always consult with healthcare professionals for medical decisions.