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.
Journal:
Atherosclerosis
Published Date:
Oct 9, 2019
Abstract
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.
Authors
Keywords
Aged
China
Coronary Stenosis
Decision Support Techniques
Female
Gene Expression Profiling
Gene Regulatory Networks
Genetic Predisposition to Disease
Humans
Male
Middle Aged
Nomograms
Phenotype
Predictive Value of Tests
Reproducibility of Results
Retrospective Studies
Risk Factors
Severity of Illness Index
Support Vector Machine
Transcriptome