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ABSTRACT: Background
With the advancement in machine learning (ML) and artificial neural networks as well as the development of portable electrocardiogram devices, artificial intelligence (AI) has been increasing in popularity over the years. In this study, we aimed to provide an overview of the research regarding the utilization of AI techniques to improve the diagnosis of arrhythmia.Methods
We extracted data published 2004 to 2021 from Web of Science database. The online analytic platform, Literature Metrology (http://bibliometric.com), was used to analyze publication trends, including information about journals, authors, institutions, collaborations between countries, citations, and keywords.Results
Keywords, such as deep learning, electrocardiogram (ECG), and convolutiona
SUBMITTER: Huang J
PROVIDER: S-EPMC9186255 | biostudies-literature | 2022 May
REPOSITORIES: biostudies-literature