Heart Disease Prediction Reimagined.
An intelligent machine learning system designed to analyze clinical indicators and estimate the likelihood of heart disease.
Cardiovascular Assessment
Powered by Logistic Regression
Machine Learning Behind the Experience.
This Heart Disease Prediction system uses clinical and medical indicators to generate a machine learning based risk assessment.
Dataset
UCI Heart Disease Dataset containing 303 patient records.
Features
13 clinical and cardiovascular indicators are used as model inputs.
Algorithm
Logistic Regression was evaluated alongside Random Forest during model development.
Built on Real Evaluation.
Logistic Regression
Evaluated against Random Forest during model development.
Analyze Clinical Indicators.
Enter the patient's clinical information below to generate a machine learning prediction.