Review demonstrates enhanced diagnostic accuracy using artificial intelligence in routine electrocardiography, highlighting improved cardiac risk stratification.
Key Points
To examine advancements in routine electrocardiography (ECG) and evaluate how modern digital technologies and artificial intelligence expand clinical diagnostics.
Synthesized current clinical applications and algorithmic innovations in standard 12-lead electrocardiogram analysis.
Evaluated diagnostic pipelines integrating deep learning architectures with traditional cardiac signal processing.
Modern computational tools detect subtle electrophysiological patterns, enabling noninvasive identification of structural heart disease and occult arrhythmias.
Enhanced algorithmic interpretation reduces diagnostic variability and accelerates clinical decision-making in diverse healthcare environments.