Abstract:21One goal of personalized medicine is leveraging the emerging tools of data science to guide medical decision-making. Achieving this using disparate data sources is most daunting for polygenic traits and requires systems level approaches. To this end, we employed random forests (RF) and neural networks (NN) for predictive modeling of coronary artery calcification (CAC), which is an intermediate end-phenotype of coronary artery disease (CAD). Model inputs were derived from advanced cases in the ClinSeq R disco… Show more
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