Advanced Ai Based Diagnostic System
Developed an AI-driven healthcare system featuring YOLOv8 for precise skin cancer detection, an AI chatbot for instant health advice, and a user-friendly interface. Leveraged Next AI SDK, OpenAI, Google Colab, Next.js, Recoil, and Tailwind CSS to deliver advanced, accessible, and innovative medical solutions.
Integrated HealthAI: Revolutionizing Healthcare through Advanced Diagnostic Systems
Project Overview
Integrated HealthAI is a comprehensive system designed to revolutionize healthcare by providing advanced diagnostic capabilities through multiple components:
- HeartBeat-Detection-using-OpenCV - An application for detecting heartbeats using computer vision techniques.
- Skin Cancer - An application for diagnosing skin cancer using machine learning models.
- Frontend - The user-facing interface for interacting with the system.
Prerequisites
General Requirements:
- Node.js and npm should be pre-installed for the frontend.
- Python (version 3.7 or above) and pip should be pre-installed for the backend components.
Setting Up the Project
1. HeartBeat-Detection-using-OpenCV
The HeartBeat-Detection-using-OpenCV
folder contains the application for heartbeat detection. To set it up:
- Navigate to the
HeartBeat-Detection-using-OpenCV
folder:cd HeartBeat-Detection-using-OpenCV
- Install the dependencies:
pip install -r requirements.txt
- Start the application:
uvicorn heartbeat:app --reload
2. Skin Cancer
The Skin Cancer
folder contains the application for diagnosing skin cancer. To set it up:
- Navigate to the
Skin Cancer
folder:cd Skin Cancer
- Install all dependencies (ensure
requirements.txt
is set up):pip install -r requirements.txt
- Start the application:
python main.py
3. Frontend
The frontend
folder contains the user-facing interface. To set it up:
- Navigate to the
frontend
folder:cd frontend
- Install the dependencies:
npm install
- Start the frontend development server:
npm run dev
Running the Project
- Ensure all components are set up according to the instructions above.
- Start the backend services (
HeartBeat-Detection-using-OpenCV
and Skin Cancer
).
- Start the frontend development server.
- Access the system through the frontend interface to utilize the diagnostic applications.
Notes
- Configure any required environment variables for each component.
- Ensure that all dependencies are installed as specified in the respective
requirements.txt
or package.json
files.
- For additional help, consult the documentation or reach out to the development team.
License
This project is licensed under the MIT License.
Transforming healthcare, one diagnostic at a time.