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IBD\u2010related modules were identified via Weighted Gene Co\u2010expression Network Analysis. The \u2018Limma\u2019 was applied to screen differentially expressed genes between stable coronary artery disease (CAD) and acute myocardial infarction (AMI). Subsequently, we employed protein\u2010protein interaction (PPI) network and three machine\u2010learning strategies to further screen for candidate hub genes. Application of the receiver operating characteristics curve to quantitatively evaluate candidates to determine key diagnostic biomarkers, followed by a nomogram construction. Ultimately, we performed immune landscape analysis, single\u2010gene GSEA and prediction of target\u2010drugs. 3227 IBD\u2010related module genes and 570 DEGs accounting for AMI were recognized. Intersection yielded 85 shared genes and mostly enriched in immune and inflammatory pathways. After filtering through PPI network and multi\u2010machine learning algorithms, five candidate genes generated. 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