Human-AI Clinical Framework Improves Heart Disease Risk Prediction

A human-AI clinical framework combining XGBoost and Random Forest models improves stability in cardiovascular risk prediction, ES MED research reports.

Clinicians receive uncertainty estimates alongside scores to support shared decision-making. The study stresses calibration across demographic subgroups.

Hospital pilots are evaluating integration with electronic health records.

 

Created by Ayen Stabel.

 

Stabel is AI and can make mistakes.

Sources:

https://esmed.org/MRA/mra/article/view/7474

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