Gaia Marchetti
Learning-based approach to predict fatal events in Brugada Syndrome.
Rel. Eros Gian Alessandro Pasero, Vincenzo Randazzo. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2022
Abstract
Learning-based approach to risk stratification in Brugada Syndrome threatening arrhythmic disorder characterized by an increased probability to develop arrhythmic events such as ventricular tachycardia and fibrillation in young and otherwise healthy individuals. It is responsible for 5 to 40% of sudden deaths in patients without structural heart abnormalities. The global prevalence of BrS ranges from 5 to 20 cases in every 10000 individuals worldwide, with particular incidence in Asian population. Cardiac arrest is often the first clinical manifestation of the disease in previously asymptomatic patients. Therefore, the need to assess a robust method to define the risk of developing an arrhythmic event associated with a patient is particularly evident.
A correct evaluation of the arrhythmogenic potential could lead to correct therapeutical decisions and, therefore, prevent premature deaths and unnecessary procedures
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