Explainable Clinical Decision Support

Explainable Heart Disease Risk Prediction

An intelligent research prototype using Gradient Boosting and SHAP to support transparent initial screening.

Start Risk PredictionLearn How It Works
Clinical dashboard

Transparent Screening

Model Ready
13Clinical parameters
GBPrediction model
SHAP explanationGlobal + Local

Clinical Risk Prediction

Processes 13 clinical parameters used by the trained prediction model.

Gradient Boosting Model

Combines 80 decision trees to estimate heart disease probability.

SHAP Explanations

Provides global importance and permutation-based local explanations.

This system supports initial screening and does not replace clinical diagnosis or professional medical judgment.