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Studies have demonstrated that the current US guidelines based on American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort Equations Risk Calculator may underestimate risk of atherosclerotic cardiovascular disease (CVD) in certain high‐risk individuals, therefore missing opportunities for intensive therapy and preventing CVD events. Similarly, the guidelines may overestimate risk in low risk populations resulting in unnecessary statin therapy. We used Machine Learning (ML) to tackle this problem.

We developed a ML Risk Calculator based on Support Vector Machines (SVMs) using a 13‐year follow up data set from MESA (the Multi‐Ethnic Study of Atherosclerosis) of 6459 participants who were atherosclerotic CVD‐free at baseline. We provided identical input to both risk calculators and compared their performance. We then used the …