🏥 AI-Driven Transcription and Analysis for Medical Conversations

📖 Overview

This repository focuses on leveraging AI-driven transcription and analysis to enhance healthcare workflows. By transcribing and analyzing doctor-patient conversations, the system integrates valuable insights into Electronic Health Records (EHR), improving documentation accuracy, reducing administrative burdens, and boosting patient outcomes.

Our solution employs advanced Natural Language Processing (NLP) and a multimodal approach to provide a holistic analysis of medical conversations.

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✨ Features

• 🎤 Real-time Transcription: Convert doctor-patient conversations into accurate text.
• 🤖 Multimodal Analysis: Combine textual and audio data for deeper insights:
  • Analyze verbal (speech-to-text) and non-verbal cues (e.g., tone, sentiment).
• 💻 EHR Integration: Seamlessly update patient records with enhanced documentation.
• 🔄 Feedback Loop: Refine accuracy and usability based on clinician input.
• 🔒 Data Privacy: Compliant with healthcare regulations like HIPAA for secure handling of sensitive data.

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🧠 Multimodal Approach

Our multimodal system enhances the analysis by integrating both text and audio data:

1. Transcribe Conversations: Accurately convert speech into text.
2. Detect Non-Verbal Cues: Analyze tone, sentiment, and rhythm to provide emotional and contextual insights.
3. Enrich Documentation: Add verbal and non-verbal analysis to EHRs, offering a comprehensive view of patient interactions.
4. Support Diagnosis: Combine speech patterns with contextual analysis for better decision-making.

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⚙️ Installation

🛠 Prerequisites

Ensure you have the following:

• Python 3.6+
• Required libraries (see requirements.txt)

Install dependencies:

pip install -r requirements.txt
🚀 Setup

Clone the repository:

git clone https://github.com/your-repo/ai-driven-transcription.git
cd ai-driven-transcription

Install required dependencies:

pip install -r requirements.txt

Run the application:

python app.py

📋 Usage Upload recorded audio files of doctor-patient conversations. The system transcribes speech into text and provides detailed analyses. Results are integrated into EHRs or exported as CSV/JSON files.

🤝 Contributing We welcome contributions to improve this project! Follow these steps:

Fork the repository. Create a feature branch:

git checkout -b feature-xyz

Commit your changes:

git commit -am "Add feature XYZ"

Push the branch:

git push origin feature-xyz

Open a Pull Request for review. 🚧 Challenges and Future Work 🛡 Data Privacy Ensuring compliance with healthcare standards like HIPAA is crucial. We're implementing:

Data anonymization End-to-end encryption 🌐 Interoperability Adapting to different EHR systems is a priority. Ongoing efforts focus on scalability and flexibility to ensure seamless integration across platforms.

📜 License This project is licensed under the MIT License. See the LICENSE file for details.

🙏 Acknowledgements Special thanks to the clinicians and developers who contributed to improving this system. Your feedback drives our innovation. ❤️