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Research output of artificial intelligence in arrhythmia from 2004 to 2021: a bibliometric analysis.

Junlin Huang | Yang Liu | Shuping Huang | Guibao Ke | Xin Chen | Bei Gong | Wei Wei | Yumei Xue | Hai Deng | Shulin Wu
Journal of thoracic disease | 2022

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.

Pubmed ID: 35693591

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PubMed (tool)

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Public bibliographic database that provides access to citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites. PubMed citations and abstracts include fields of biomedicine and health, covering portions of life sciences, behavioral sciences, chemical sciences, and bioengineering. Provides access to additional relevant web sites and links to other NCBI molecular biology resources. Publishers of journals can submit their citations to NCBI and then provide access to full-text of articles at journal web sites using LinkOut.

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Data analytics company that operates a collection of services: Web of Science (EndNote, InCites, Journal Citation Reports, Publons, Kopernio), Cortellis, Derwent, Derwent World Patents Index, CompuMark, MarkMonitor, Techstreet, Publons, EndNote, Kopernio, and ScholarOne. Deliver critical data, information, workflow solutions and deep domain expertise to innovators everywhere.

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