PhiloHeart AI is an advanced, interactive, deep learning powered web application designed for predicting the risk of heart attacks using clinical data as it features a professional UI, real time prediction, diffrent forms of visualizations and also an intelligent chatbot

• Patient Intake: Interactive sidebar for entering clinical and demographic data
• Prediction Engine: Real time heart attack risk predictions using Extra Trees Classifier
• Deep Learning Model: TensorFlow based ANN for evaluation and analysis
• Data Insight: Exploratory data analysis and visualizations
• Model Comparison: Accuracy, AUC, ROC curves, confusion matrix
• Trend Tracking: Longitudinal risk trends for patients
• Export Records: Generate CSV reports for EHR integration
• AI Assistant: Context aware chatbot which is powered by Groq's LLaMA 3

.
├── app.py                      # Main Streamlit app
├── synthetic_heart_disease.csv  # Synthetic dataset used for testing
├── et_model.pkl               # Trained Extra Trees model
├── ann_model.pkl              # Trained ANN model (optional)
├── ann_history.pkl            # ANN training history (optional)

**Nairrah Nawar Ahmed – Model Development & ML Engineering

**Teja K – Frontend & Backend Streamlit Developer and ML Engineering

IMPORTANT: This tool is not intended for clinical or diagnostic use or any medical environment and soley for TEST PURPOSES ONLY

PhiloHeart AI is for educational research and is coded for "CS base - Hack4Health" hackathon It is based on synthetic data and has not been validated against real world clinical datasets Do not use this tool for actual patient diagnosis, treatment or decision making since this is purley for testing purposes Always consult healthcare professionals for medical advice and decisions