Abstract
In addition to ambulatory heart rhythm monitors (Holter ECG), several other types of devices such as smart watches, smartphones, and insertable cardiac monitors also contribute to making the diagnosis and management of arrhythmias more convenient. However, the processing of filtering data and analysis of the huge amount of electrocardiogram (ECG) data from these devices cannot be done manually but requires the help of artificial intelligence (AI).
The application of AI in ECG and Holter ECG data analysis not only helps reduce the workload of ECG analysis physicians but also supports faster and more accurate diagnosis. Some studies show that automated AI analysis combined with other clinical information can suggest clinical prognosis of cardiac events related to arrhythmias and monitor response of treatment more effectively.
AI technology has advanced significantly and is increasingly being utilized in the treatment of complex arrhythmias, including atrial fibrillation (AF) and ventricular tachycardia (VT). Initial clinical intervention studies have shown that the application of AI can help to identify targeted/ interested zones of arrhythmias for ablation, improve intervention outcomes, shorten intervention times, but not increase the risk of complications.