Version: v1.0.1 (Bug Fixes)
HeartPal is a cardiovascular risk awareness tool built with Python and Streamlit. It uses a logistic regression model trained on real health data to estimate your heart disease risk and track how it changes over time.
Heart disease runs in my family. Watching my dad manage his health made me realize how little most people understand about their own cardiovascular risk — and how small lifestyle changes, tracked consistently, can actually make a difference.
HeartPal isn't a medical tool. It's an awareness tool. Something you check once a month, see your risk score, and understand which factors are driving it.
- Monthly risk assessment — 21-question health questionnaire covering lifestyle, medical history, and demographics
- ML-powered scoring — logistic regression model trained on the CDC BRFSS dataset
- Personalized risk factors — shows which of your inputs are contributing most to your score
- Risk history chart — tracks your score over time so you can see progress
- Lightweight and private — no accounts, no passwords, just your name
- Python
- Streamlit
- scikit-learn (Logistic Regression)
- SQLite
- Plotly
- pandas / NumPy
git clone https://github.com/yourusername/HeartPal.git
cd HeartPal
pip install -r requirements.txt
python -m streamlit run Home.pyTrained on the CDC BRFSS Health Indicators Dataset — a survey of over 250,000 Americans on health behaviors and conditions.
HeartPal is for educational and awareness purposes only. It is not a substitute for professional medical advice, diagnosis, or treatment.
- First load of the questionnaire may take slightly longer due to model initialization. Subsequent loads are typically faster.
Built for the 2025 Congressional App Challenge — Arizona's 1st Congressional District.