Limitations and Challenges of AI-ECG

Cardiovascular and metabolic diseases stand as significant contributors to global mortality. The current approach to assessing electrocardiograms (ECGs) involves a combination of human analysis and automated machine readings. However, these methods are restricted in their ability to extract complex information from ECGs, underscoring the potential for AI advancements to enhance ECG analysis. Novel algorithms rooted in machine learning and deep learning offer promise in complementing traditional ECG evaluation methods. While recent studies exhibit the feasibility of AI-ECG algorithms for detection, it is vital to acknowledge the distinct challenges and limitations they entail. This chapter aims to cultivate reader understanding and awareness of AI systems, with a focus on addressing present challenges.