Key result
AI enhances precision and automation in diagnosing arrhythmias and SCD to improve urgent decision-making.
Why the study?
The rapid evolution of AI in arrhythmias and sudden cardiac death necessitates ensuring that progress is grounded in sound scientific evidence alongside urgent, accurate clinical decision-making.
Design
Overview with illustrative case examples
Supports AI incorporation into arrhythmia workflows; extends evidence on ML applications in SCD management.
The use of artificial intelligence (AI) in medical science has seen a rapid evolution, especially in the last few years. The use of AI in the field of arrhythmias and sudden cardiac death is especially relevant given the need for urgent, accurate decision-making in these clinical scenarios. AI and machine learning have heralded a new era in improving the precision and automation of diagnosis in arrhythmias ranging from ventricular tachycardia, atrial fibrillation, and bradyarrhythmias. However, the rapid pace of developments in this field also calls for caution in ensuring that progress is based on sound scientific evidence. This paper provides an overview of the basics of AI for clinicians and considers some key applications of AI in the field of arrhythmias through illustrative case examples.
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Sandro Ninni (2025) studied this question. AI enhances precision and automation in diagnosing arrhythmias and sudden cardiac death, improving urgent decision-making in clinical scenarios.
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