Open AccessBig Data and Artificial Intelligence: Opportunities and Threats in Electrophysiology
Author(s) -
Rutger R van de Leur,
Machteld Boonstra,
Ayoub Bagheri,
Rob W Roudijk,
Arjan Sammani,
Karim Taha,
Pieter A. Doevendans,
Pim van der Harst,
Peter M. van Dam,
Rutger J. Hassink,
René van Es,
Folkert W. Asselbergs
Publication year - 2020
Publication title -
arrhythmia and electrophysiology review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.008
H-Index - 18
eISSN - 2050-3377
pISSN - 2050-3369
DOI - 10.15420/aer.2020.26
Subject(s) - cardiac electrophysiology , computer science , narrative review , clinical electrophysiology , artificial intelligence , modalities , big data , data science , electrophysiology , field (mathematics) , medicine , neuroscience , psychology , intensive care medicine , data mining , social science , mathematics , sociology , pure mathematics
The combination of big data and artificial intelligence (AI) is having an increasing impact on the field of electrophysiology. Algorithms are created to improve the automated diagnosis of clinical ECGs or ambulatory rhythm devices. Furthermore, the use of AI during invasive electrophysiological studies or combining several diagnostic modalities into AI algorithms to aid diagnostics are being investigated. However, the clinical performance and applicability of created algorithms are yet unknown. In this narrative review, opportunities and threats of AI in the field of electrophysiology are described, mainly focusing on ECGs. Current opportunities are discussed with their potential clinical benefits as well as the challenges. Challenges in data acquisition, model performance, (external) validity, clinical implementation, algorithm interpretation as well as the ethical aspects of AI research are discussed. This article aims to guide clinicians in the evaluation of new AI applications for electrophysiology before their clinical implementation.