AI-Enhanced ECG Screenings: An Alternative to Traditional Questionnaires for Ischaemic Heart Disease

Ischaemic heart disease (IHD) is the leading global cause of death. Traditional screening tools like the Framingham Risk Score (FRS) and Systematic Coronary Risk Evaluation (SCORE), often based on questionnaires, face criticism for subjectivity, limited generalisability to diverse populations (especially in low- and middle-income countries, LMICs), and difficulty detecting subclinical disease. This commentary explores the potential of artificial intelligence-enhanced electrocardiogram (AI + ECG) analysis as a superior alternative. AI + ECG leverages objective electrophysiological data, offering automated, potentially more accurate, cost-effective, and accessible risk stratification, particularly valuable in resource-constrained settings where 80% of cardiovascular deaths occur. Evidence suggests AI + ECG models outperform traditional methods in various diagnostic tasks and show promise in cost-effectiveness. However, significant gaps remain, primarily the need for validation in diverse global populations, especially LMICs. This paper argues for a policy shift towards AI + ECG screenings, advocating for urgent, large-scale validation trials, development of ethical and regulatory frameworks, and sustained funding to democratise early IHD detection and reduce global mortality.