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❤️ CardioAI Predictor

Advanced AI-Powered Heart Disease Risk Assessment
Powered by OnePersonAI Technologies


📌 Overview

CardioAI Predictor is an AI-powered web application that helps assess the probability of heart disease risk based on patient medical data.
It uses machine learning models and interactive visualizations to provide insightful predictions, while ensuring data privacy and local processing.

Disclaimer:
This tool is for educational and informational purposes only.
It is NOT a substitute for professional medical advice, diagnosis, or treatment. Always consult a qualified healthcare provider for any medical concerns.


🚀 Features

  • 🧠 AI-Powered Predictions – Uses Random Forest ML model trained on clinical datasets.
  • 📊 Risk Visualization Dashboard – Interactive charts for probability, risk distribution, and confidence level.
  • 🔍 SHAP Explainability – Understand how each feature impacts predictions.
  • 🛡 Privacy First – No data storage; all processing happens locally.
  • 📈 Continuous Learning – Model adapts and improves over time.

📷 Screenshots

1️⃣ Home & Data Entry

Home

2️⃣ Detailed Probability Analysis

Analysis

3️⃣ About & Technology

About


🛠 Tech Stack

  • Frontend: Streamlit
  • Backend: Python, scikit-learn
  • Visualization: Matplotlib, Plotly
  • Explainability: SHAP
  • Model: Random Forest Classifier

📥 Installation

  1. Clone the repository
    git clone https://github.com/yourusername/cardioai-predictor.git
    cd cardioai-predictor

2. **Create and activate a virtual environment**

   ```bash
   python -m venv venv
   source venv/bin/activate  # For Linux/Mac
   venv\Scripts\activate     # For Windows
   ```

3. **Install dependencies**

   ```bash
   pip install -r requirements.txt
   ```

4. **Run the app**

   ```bash
   streamlit run app.py
   ```

---

## 📊 How It Works

1. **Input Patient Data** – Age, gender, chest pain type, vital signs, etc.
2. **AI Model Prediction** – Model calculates the probability of heart disease.
3. **Risk Dashboard** – Displays probability charts, distribution, and confidence.
4. **Explainability** – SHAP values help interpret feature contributions.

---

## 📜 License

This project is licensed under the **MIT License**.

---

## 📧 Contact

For technical support: **[support@onepersonai.com](mailto:support@onepersonai.com)**
For emergencies: **Call 911**

---

### ✨ Developed by OnePersonAI Technologies
<img width="1920" height="1080" alt="Screenshot 2025-08-13 012207" src="https://github.com/user-attachments/assets/8c6f4d38-6810-4d82-a9ee-fe03012dacd1" />


**Advancing healthcare through artificial inte<img width="1920" height="1080" alt="Screenshot 2025-08-13 012224" src="https://github.com/user-attachments/assets/eb4ba3aa-5aba-4b62-8ae6-a7bb1352055b" />
lligence**
<img width="1920" height="1080" alt="Screenshot 2025-08-13 012240" src="https://github.com/user-attachments/assets/5e8e78f7-06d7-49cf-9965-d97e7776a576" />

About

Heart Disease Prediction App This is a machine learning-powered web app designed to help users estimate their risk of heart disease based on health parameters. It integrates data science, predictive modeling, and intuitive UI/UX to deliver insights in minutes.

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