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Cardiology turns to interpretable machine learning as the demand for explainable risk tools grows

A Nature paper on stroke risk prediction in newly diagnosed atrial fibrillation underscores the field’s shift toward interpretable models. In cardiology, where decisions often hinge on trust and risk communication, explainability may matter almost as much as predictive power.