KRİSHNA MOHAN SURAPANENİ
International Journal of Medical Biochemistry - 2025;8(2):151-154
The timely and accurate diagnosis of acute coronary syndrome (ACS) is essential for improving patient outcomes, as delayed treatment can result in irreversible myocardial damage and increased mortality. Many studies investigated the feasibility and efficacy of artificial intelligence (AI)-based wearable technologies for the non-invasive, point-of-care assessment of high-sensitivity cardiac troponins (hs-cTn), a critical biomarker for myocardial injury. These wearables combine advanced biosensors with machine learning algorithms to deliver real-time, accurate hs-cTn measurements, enabling faster and more effective clinical decision-making. Clinical trials reveal that AI-powered wearables achieve diagnostic accuracy comparable to traditional laboratory assays while significantly reducing diagnostic time and resource burden. Additionally, their portability and cost-effectiveness make them suitable for diverse healthcare settings, including remote and resource-limited environments. This opinion paper seeks to elaborate on the insights gained from this study, emphasizing the transformative potential of AI-driven wearables in enhancing ACS diagnosis, streamlining patient care, and reducing strain on healthcare systems.
