News
Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases
Oct 08, 2025
Our latest article, “Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases“,
published in Circulation Research, and American Heart Association’s Basic Cardiovascular Sciences Scientific Sessions 2025: Advances in Cardiovascular Science: From Discovery to Translation.
Abstract:
Cardiovascular diseases (CVDs) are complex, multifactorial conditions that require personalized assessment and treatment. Advancements in multi-omics technologies, most importantly whole-genome sequencing (WGS) and RNA sequencing (RNA-seq) have provided translational researchers with a comprehensive view of the human genome and transcriptome. The efficient synthesis and analysis of multimodal data that characterizes genetic variants alongside expression patterns linked to emerging phenotypes, can reveal novel biomarkers and enable the segmentation of patient populations based on personalized risk factors. In this study, we present a cutting-edge and groundbreaking methodology rooted in the integration of traditional bioinformatics, classical statistics, and multimodal artificial intelligence (AI) and machine learning (ML) techniques. Our approach has the potential to uncover the intricate mechanisms underlying CVD, enabling patient-specific risk and response profiling … … …
Publication/Citation:
- DeGroat, W., Narayanan, R., Peker, E., Zeeshan, S., Liang, B.T., and Ahmed, Z*. (2025). Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases. Circulation Research, Vol. 137 (Suppl_1). American Heart Association’s Basic Cardiovascular Sciences Scientific Sessions 2025: Advances in Cardiovascular Science: From Discovery to Translation. AHA/ASA (American Heart Association/American Stroke Association)