Artificial intelligence for electrocardiography: Applications to vectorcardiography in myocardial infarction

Heart attacks, or myocardial infarctions (MI), pose a major global health challenge. Quick diagnosis and treatment are critical to saving lives and improving recovery outcomes. Yet, access to sufficiently experienced health care staff is limited in many regions, especially in developing countries. This research focuses on automating the detection and localisation of MI using artificial intelligence and electrocardiography (ECG), a common tool that records the heart’s electrical activity.
Automated systems can make MI diagnosis faster, more accurate, and accessible. By reducing treatment delays, these methods improve patient outcomes and ease the strain on healthcare systems. Crucially, the developed techniques are simple, cost-effective, and compatible with wearable devices, enabling heart attack detection in daily life.
By analysing the heart's electrical signals using electrodes attached to the skin, these methods pinpoint where a heart attack occurs, aiding effective treatment. They empower less experienced healthcare workers to triage patients efficiently, bridging gaps in care. Beyond MI, these innovations could advance other biomedical technologies, offering broader benefits. Ultimately, this research marks a significant step towards improving global heart health and advancing accessible medical solutions.