Researchers at the Icahn School of Medicine at Mount Sinai developed a computer-derived marker for coronary artery disease (CAD) using machine learning and clinical data from electronic health records (EHRs), mapping CAD characteristics on a spectrum for the first time.
The machine learning model ISCAD (In Silico Score for Coronary Artery Disease) was trained on 95,935 EHRs from the BioMe Biobank of the Mount Sinai Health System and the U.K. Biobank.
The model includes hundreds of different clinical features, while the existing clinical score for CAD incorporates a much smaller number of predetermined features.
The researchers found the model's probabilities accurately tracked the degree of coronary stenosis, mortality, and complications like heart attack.
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Abstracts Copyright © 2022 SmithBucklin, Washington, DC, USA
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