DocPilot

DocPilot is a Flutter application designed to assist healthcare providers in recording, transcribing, and analyzing doctor-patient conversations. It leverages voice recognition, natural language processing, and AI to streamline medical documentation workflows.

Features

• Voice Recording: Capture doctor-patient conversations with a simple, intuitive interface
• Real-time Voice Transcription: Convert spoken conversations to text using Deepgram's Nova-2 model
• AI-Powered Analysis: Process transcribed conversations with Google's Gemini to generate:
  • Conversation summaries
  • Prescription suggestions
• Elegant UI: Beautiful gradient design with animated waveform visualization
• Export & Share: Save and share prescriptions with patients or other healthcare providers

Getting Started

Prerequisites

• Flutter SDK (latest version recommended)
• Dart SDK
• Android Studio / VS Code with Flutter extensions
• API keys for:
  • Deepgram (for speech-to-text)
  • Google Gemini (for AI processing)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/docpilot.git
   cd docpilot

2. Install dependencies:

   flutter pub get

3. Create a .env file in the root directory with your API keys:

   DEEPGRAM_API_KEY=your_deepgram_api_key
   GEMINI_API_KEY=your_gemini_api_key
   

4. Run the app:

   flutter run

Project Structure

lib/
├── main.dart             # App entry point and main screen
├── screens/
│   ├── transcription_detail_screen.dart    # Displays raw transcription
│   ├── summary_screen.dart                 # Displays AI-generated summary
│   ├── prescription_screen.dart            # Displays AI-generated prescription
└── services/
    └── chatbot_service.dart                # Handles Gemini API integration

How It Works

1. Recording: The app uses the record package to capture audio from the device's microphone.
2. Transcription: Recorded audio is sent to Deepgram's API for accurate speech-to-text conversion.
3. AI Processing: The transcription is sent to Google's Gemini AI for:
   • Generating a concise summary of the medical conversation
   • Creating a prescription based on the conversation content
4. Visualization: Results are displayed in separate screens with Markdown formatting for better readability.
5. Export: Prescriptions can be saved and shared with the patient via various apps.

Dependencies

• flutter_dotenv: For managing environment variables
• record: For audio recording
• path_provider: For file management
• permission_handler: For handling device permissions
• http: For API requests
• flutter_markdown: For rendering formatted text
• share_plus: For sharing functionality

Permissions

The app requires the following permissions:

• Microphone: For recording audio
• Storage: For saving prescriptions (Android)

Customization

You can customize the app by:

• Modifying the theme colors in main.dart
• Adjusting the recording parameters in the _startRecording() method
• Changing the Gemini prompts in the _processWithGemini() method to get different outputs

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Deepgram for speech-to-text capabilities
• Google Gemini for AI processing
• Flutter team for the amazing framework

Future Enhancements

• Multi-language support
• Patient history integration
• Cloud synchronization
• Custom AI model fine-tuning for medical terminology
• Appointment scheduling integration
• Medical image analysis