The Role of Artificial Intelligence in Arrhythmia Monitoring.
Arrhythmia
Artificial intelligence
Electrocardiography
Machine learning
Monitoring
Journal
Cardiac electrophysiology clinics
ISSN: 1877-9190
Titre abrégé: Card Electrophysiol Clin
Pays: United States
ID NLM: 101549998
Informations de publication
Date de publication:
09 2021
09 2021
Historique:
entrez:
31
7
2021
pubmed:
1
8
2021
medline:
26
10
2021
Statut:
ppublish
Résumé
Arrhythmia management has been revolutionized by the ability to monitor the cardiac rhythm in a patient's home environment in real-time using high-fidelity prescription-grade and commercially available wearable electrodes. The vast amount of digitally acquired electrophysiological signals has generated the need for scalable and efficient data processing with actionable output that can be provided directly to clinicians and patients. In this setting, artificial intelligence applications are increasingly important in arrhythmia monitoring, ranging from conventional algorithmic analysis for rhythm determination to more complex deep machine learning methods that have led to the realization of fully automated humanlike rhythm determination in real-time.
Identifiants
pubmed: 34330380
pii: S1877-9182(21)00042-3
doi: 10.1016/j.ccep.2021.04.011
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
543-554Informations de copyright
Copyright © 2021 Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Disclosure Mayo Clinic, K.C.S., and P.A.F. have filed patents on AI-ECG algorithms discussed in this article.