aceMachine learning and multi-omics technologies for precision cardiovascular medicine: advancing diagnosis, risk prediction, and therapeutic guidance
Cardiovascular disease remains a major global health burden. Owing to its complex pathogenesis and marked clinical heterogeneity, conventional one-size-fits-all strategies often yield limited benefit for a substantial proportion of patients. Precision medicine advocates individualized management based on patients' clinical and molecular characteristics to improve outcomes. In this context, multi-omics and machine learning provide critical technical support for precision medicine: multi-omics can capture the full…
Integration of multi-omics and machine learning can improve cardiovascular disease management by supporting definitive and early diagnosis, severity assessment, full-course risk stratification, and individualized prediction of drug and surgical benefit-risk to inform decisions.
Clinical translation is constrained by unresolved issues around data quality, model validation, transparency, accountability, and implementation and cost coverage policies.
Evidence
- Peer-reviewedFrontiers in Cardiovascular Medicine2026-08-13
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Truvace Impact Record TRV-2026-0784, v1: “Machine learning and multi-omics technologies for precision cardiovascular medicine: advancing diagnosis, risk prediction, and therapeutic guidance.” Truvace, 2026-08-16. /record/TRV-2026-0784 (accessed at citation time). sha256 81f126871ea4a274…
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