Evidence map›Paper›PMID 38433757›Full record

ArticleFrontiers in cardiovascular medicine2024

Artificial intelligence applied in cardiovascular disease: a bibliometric and visual analysis.

Jirong Zhang, Jimei Zhang, Juan Jin, Xicheng Jiang, Linlin Yang, Shiqi Fan, Qiao Zhang, Ming Chi

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jirong Zhang *Graduate School, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, China.
Jimei Zhang *College of Public Health, The University of Sydney, NSW, Sydney, Australia.
Juan JinThe First Department of Cardiovascular, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, HL, China.
Xicheng JiangCollege of basic medicine, Heilongjiang University of Chinese Medicine, Harbin, HL, China.
Linlin YangCardiovascular Disease Branch, Dalian Second People's Hospital, Dalian, LN, China.
Shiqi FanHarbin hospital of traditional Chinese medicine, Harbin, HL, China.
Qiao ZhangSchool of Pharmacy, Harbin University of Commerce, Harbin, HL, China.
Ming ChiGraduate School, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the rapid development of technology, artificial intelligence (AI) has been widely used in the diagnosis and prognosis prediction of a variety of diseases, including cardiovascular disease. Facts have proved that AI has broad application prospects in rapid and accurate diagnosis. Objective: This study mainly summarizes the research on the application of AI in the field of cardiovascular disease through bibliometric analysis and explores possible future research hotpots. Methods: The articles and reviews regarding application of AI in cardiovascular disease between 2000 and 2023 were selected from Web of Science Core Collection on 30 December 2023. Microsoft Excel 2019 was applied to analyze the targeted variables. VOSviewer (version 1.6.16), Citespace (version 6.2.R2), and a widely used online bibliometric platform were used to conduct co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references, and keywords in this field. Results: A total of 4,611 articles were selected in this study. AI-related research on cardiovascular disease increased exponentially in recent years, of which the USA was the most productive country with 1,360 publications, and had close cooperation with many countries. The most productive institutions and researchers were the Cedar sinai medical center and Acharya, Ur. However, the cooperation among most institutions or researchers was not close even if the high research outputs. Conclusions: AI has broad application prospects in cardiovascular disease, and a growing number of scholars are devoted to AI-related research on cardiovascular disease. Cardiovascular imaging techniques and the selection of appropriate algorithms represent the most extensively studied areas, and a considerable boost in these areas is predicted in the coming years.

Indexed as

artificial intelligencebibliometriccardiovascular diseaselate gadolinium enhancementLeft Ventricle Ejection Fraction (LVEF)

Identifiers

PMID38433757
PMCPMC10904648

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.