A machine learning model using Agatston score, eight calcium-omics features, and age from non-contrast CTCS predicts myocardial ischemia with 98.9% precision and 79.2% sensitivity in a single-center cohort of 987 patients.
Journal of Cardiovascular Computed Tomography 19:224–231
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Quantitative coronary calcification analysis for prediction of myocardial ischemia using non-contrast CT calcium scoring
A machine learning model using Agatston score, eight calcium-omics features, and age from non-contrast CTCS predicts myocardial ischemia with 98.9% precision and 79.2% sensitivity in a single-center cohort of 987 patients.