An advanced AI-powered health monitoring and early disease detection system. This platform helps users and healthcare professionals predict and detect critical health conditions, including Heart Failure, Coronary Artery Stenosis, and Mouth Cancer using state-of-the-art Machine Learning models.

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📺 Live Demo

Experience the system in action: Watch the Live Demo Video on Google Drive

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🔍 Key Modules & Features

1. Heart Failure Prediction & Assessment

Predicts the risk level and risk score of heart failure based on user-entered symptoms and health checkup parameters.

• Input: Health metrics and symptoms.

• Output: Risk percentage, detailed assessment, and actionable insights.

  Frontend

Heart Failure Prediction

2. Coronary Artery Stenosis Detection

Assists cardiologists and radiologists in identifying early-stage blockages in coronary arteries, potentially preventing heart attacks.

• Model: YOLOv11 (You Only Look Once)

• Visual Output: Bounding boxes identifying stenotic regions.

  Stenosis Detection

3. Mouth (Oral) Cancer Detection

Facilitates early identification of malignant oral tissues, which is key to improving survival rates.

• Model: YOLOv11

• Significance: Aids in detecting abnormalities early when the 5-year survival rate is highest.

  Mouth (Oral) Cancer Detection

4. Interactive Chatbot & Reports

• AI Chatbot: Real-time responses to health queries.
• Report Generation: Export and download detailed clinical summaries.

  AI Chatbot

Report Generation

🛠️ Technology Stack

• Backend: Python, Flask
• Frontend: HTML5, CSS3 (Vanilla), JavaScript
• Machine Learning / AI: YOLOv11, Scikit-learn

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⚙️ Installation & Setup

Follow these steps to set up the project locally on your machine:

1. Clone the Repository

git clone https://github.com/plk456/AI-Based-Health-Monitoring-System.git
cd AI-Based-Health-Monitoring-System

2. Create a Virtual Environment

python -m venv myvenv

3. Activate the Virtual Environment

• Windows (PowerShell):

  myvenv\Scripts\Activate.ps1

• Windows (Command Prompt):

  myvenv\Scripts\activate.bat

• Linux/macOS:

  source myvenv/bin/activate

4. Install Dependencies

pip install -r requirements.txt

5. Run the Application

python app.py

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📊 Summary & Statistics

• Coronary Artery Disease (CAD): Coronary artery stenosis is a major cause of death globally. Early detection is critical to preventing myocardial infarction.
• Mouth Cancer: Globally, oral cancer causes approximately 177,757 deaths every year, with a 5-year mortality rate close to 50%. Early detection via object detection models like YOLOv11 drastically improves prognosis.

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📜 License

This project is licensed under the MIT License.

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📞 Contact

• Developer: Likith Kumar
• Email: Kumarlikith178@gmail.com