Echo state networks for the recognition of type 1 Brugada syndrome from conventional 12-LEAD ECG

Echo state networks for the recognition of type 1 Brugada syndrome from conventional 12-LEAD ECG

Artificial Intelligence (AI) applications and Machine Learning (ML) methods have gained much attention in recent years for their ability to automatically detect patterns in data without being explicitly taught rules. Specific features characterise the ECGs of patients with Brugada Syndrome (BrS); ho...

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Bibliographic Details
Main Authors: Federico Vozzi, Luca Pedrelli, Giovanna Maria Dimitri, Alessio Micheli, Elisa Persiani, Marcello Piacenti, Andrea Rossi, Gianluca Solarino, Paolo Pieragnoli, Luca Checchi, Giulio Zucchelli, Lorenzo Mazzocchetti, Raffaele De Lucia, Martina Nesti, Pasquale Notarstefano, Maria Aurora Morales
Format: Article
Language:English
Published: Elsevier 2024-02-01
Series:Heliyon
Subjects:
Brugada syndrome
ECG
Machine learning
Echo state network
Online Access:http://www.sciencedirect.com/science/article/pii/S240584402401435X

Internet

http://www.sciencedirect.com/science/article/pii/S240584402401435X

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