Advanced Ai Based Diagnostic System

nimartalohana

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.

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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.

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