Determining a minimum set of variables for machine learning cardiovascular event prediction: results from REFINE SPECT registry

Abstract

Reduced ML models, including a minimum set of manually collected or imaging variables, achieved slightly lower accuracy compared to a full ML model but outperformed standard interpretation methods and risk models. ML models with fewer collected variables may be more practical for clinical implementation.