Adding global electric heterogeneity features derived from standard ECGs to risk factors improves machine learning prediction of cardiovascular events in a tertiary cardiology referral cohort.
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Evaluating the Efficacy of Vectocardiographic and ECG Parameters for Efficient Tertiary Cardiology Care Allocation Using Decision Tree Analysis
Adding global electric heterogeneity features derived from standard ECGs to risk factors improves machine learning prediction of cardiovascular events in a tertiary cardiology referral cohort.