Artificial Intelligence ECG Analysis in Patients with Short QT Syndrome to Predict Life-Threatening Arrhythmic Events
Articolo
Data di Pubblicazione:
2023
Abstract:
Short QT syndrome (SQTS) is an inherited cardiac ion channel disease related to an increased risk of sudden cardiac death (SCD) in young and otherwise healthy individuals. SCD is often the first clinical presentation in patients with SQTS. However, arrhythmic risk stratification is presently unsatisfactory in asymptomatic patients. In this context, artificial intelligence-based electrocardiogram (ECG) analysis has never been applied to refine risk stratification in patients with SQTS. The purpose of this study was to analyze ECGs from SQTS patients with the aid of different AI algorithms to evaluate their ability to discriminate between subjects with and without documented life-threatening arrhythmic events.
Tipologia CRIS:
03A-Articolo su Rivista
Keywords:
Artificial Intelligence; Shallow Learning; Deep Learning; Short QT syndrome; Electrocardiogram; Sudden Cardiac Death; Risk Stratification; Vision Transformers
Elenco autori:
Eros Pasero; Fiorenzo Gaita; Vincenzo Randazzo; Pierre Meynet; Sergio Cannata; Philippe Maury; Carla Giustetto
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