aceArtificial Intelligence for Cardiac Ischemia Detection: A Review of Biosensor, Biomarker, and Imaging Applications
Ischemic heart disease is the leading cause of global mortality, yet accurate and timely detection remains constrained by incomplete signal capture, noise, operator dependence, and imperfect reference standards. Artificial intelligence (AI) may enhance cardiovascular sensing by extracting latent diagnostic information from routinely acquired signals. This narrative review examines AI-enabled approaches to ischemia detection across three sensing modalities: the electrocardiogram as a bioelectric sensor, cardiac t…
AI can pull latent diagnostic information from routinely acquired cardiac signals, which could improve ischemia detection where noise, operator dependence and incomplete signal capture limit accuracy.
Most evidence comes from retrospective, often single-center diagnostic-performance studies, with little evidence on workflow, patient outcomes or cost, so clinical benefit remains unproven.
Evidence
- Peer-reviewedSensors2026-10-14
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Truvace Impact Record TRV-2026-1434, v1: “Artificial Intelligence for Cardiac Ischemia Detection: A Review of Biosensor, Biomarker, and Imaging Applications.” Truvace, 2026-10-15. /record/TRV-2026-1434 (accessed at citation time). sha256 9d80da042b458cd1…
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