Polygenic risk scores outperform machine learning methods in predicting coronary artery disease status.

Abstract excerpt

Coronary artery disease (CAD) is the leading global cause of mortality and has substantial heritability with a polygenic architecture. Recent approaches of risk prediction were based on polygenic risk scores (PRS) not taking possible nonlinear effects into account and restricted in that they focused on genetic loci associated with CAD, only. We benchmarked PRS, (penalized) logistic regression, naïve Bayes (NB),...

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• Bayes Theorem
• Benchmarking
• Coronary Artery Disease
• Machine Learning
• Multifactorial Inheritance