Identification of a blood-based 12-gene signature that predicts the severity of coronary artery stenosis: An integrative approach based on gene network construction, Support Vector Machine algorithm, and multi-cohort validation.

Abstract excerpt

BACKGROUND AND AIMS: We aimed to identify a blood-based gene expression score (GES) to predict the severity of coronary artery stenosis in patients with known or suspected coronary artery disease (CAD) by integrative use of gene network construction, Support Vector Machine (SVM) algorithm, and multi-cohort validation. METHODS: In the discovery phase, a public blood-based microarray dataset of 110 patients with...

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