dannydave/Heart-Disease-Diagnosis-using-Machine-Learning-and-Data-Mining

Heart Disease Diagnosis using Machine Learning and Data Mining

14
/ 100
Experimental

This project helps medical professionals quickly assess a patient's risk of heart disease. It takes common clinical measurements like age, sex, cholesterol, and blood pressure, and then predicts whether the patient is likely to have heart disease. It's designed for healthcare practitioners, doctors, or clinical researchers who need an easy way to get an early indication of heart disease risk.

No commits in the last 6 months.

Use this if you are a clinician or researcher seeking a tool to predict heart disease risk from patient clinical data for early detection and decision support.

Not ideal if you need a diagnostic tool for definitive medical decisions or a system that incorporates real-time sensor data.

cardiology patient-risk-assessment clinical-diagnosis medical-prediction healthcare-analytics
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 0 / 25

How are scores calculated?

Stars

7

Forks

Language

Jupyter Notebook

License

Last pushed

Aug 09, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/dannydave/Heart-Disease-Diagnosis-using-Machine-Learning-and-Data-Mining"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.