Adopting artificial intelligence in cardiovascular medicine: a scoping review.

Artificial intelligence Cardiovascular medicine Deep learning Machine learning

Journal

Hypertension research : official journal of the Japanese Society of Hypertension

ISSN: 1348-4214

Titre abrégé: Hypertens Res

Pays: England

ID NLM: 9307690

Informations de publication

Date de publication:
31 Oct 2023

Historique:

received: 01 04 2023

accepted: 26 09 2023

revised: 03 09 2023

medline: 1 11 2023

pubmed: 1 11 2023

entrez: 1 11 2023

Statut: aheadofprint

Résumé

Recent years have witnessed significant transformations in cardiovascular medicine, driven by the rapid evolution of artificial intelligence (AI). This scoping review was conducted to capture the breadth of AI applications within cardiovascular science. Employing a structured approach, we sourced relevant articles from PubMed, with an emphasis on journals encompassing general cardiology and digital medicine. We applied filters to highlight cardiovascular articles published in journals focusing on general internal medicine, cardiology and digital medicine, thereby identifying the prevailing trends in the field. Following a comprehensive full-text screening, a total of 140 studies were identified. Over the preceding 5 years, cardiovascular medicine's interplay with AI has seen an over tenfold augmentation. This expansive growth encompasses multiple cardiovascular subspecialties, including but not limited to, general cardiology, ischemic heart disease, heart failure, and arrhythmia. Deep learning emerged as the predominant methodology. The majority of AI endeavors in this domain have been channeled toward enhancing diagnostic and prognostic capabilities, utilizing resources such as hospital datasets, electrocardiograms, and echocardiography. A significant uptrend was observed in AI's application for omics data analysis. However, a clear gap persists in AI's full-scale integration into the clinical decision-making framework. AI, particularly deep learning, has demonstrated robust applications across cardiovascular subspecialties, indicating its transformative potential in this field. As we continue on this trajectory, ensuring the alignment of technological progress with medical ethics becomes crucial. The abundant digital health data today further accentuates the need for meticulous systematic reviews, tailoring them to each cardiovascular subspecialty.

Identifiants

DOI: 10.1038/s41440-023-01469-7 PMID: 37907600

pubmed: 37907600

doi: 10.1038/s41440-023-01469-7

pii: 10.1038/s41440-023-01469-7

doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

Informations de copyright

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