Artificial intelligence applied in cardiovascular disease: a bibliometric and visual analysis
BackgroundWith 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.Object...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-02-01
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| Series: | Frontiers in Cardiovascular Medicine |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fcvm.2024.1323918/full |
| _version_ | 1797305200136945664 |
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| author | Jirong Zhang Jimei Zhang Juan Jin Xicheng Jiang Linlin Yang Shiqi Fan Qiao Zhang Ming Chi |
| author_facet | Jirong Zhang Jimei Zhang Juan Jin Xicheng Jiang Linlin Yang Shiqi Fan Qiao Zhang Ming Chi |
| author_sort | Jirong Zhang |
| collection | DOAJ |
| description | BackgroundWith 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.ObjectiveThis 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.MethodsThe 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.ResultsA 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. Circulation is the journal with the largest number of publications in this field. The most important keywords are “classification”, “diagnosis”, and “risk”. Meanwhile, the current research hotpots were “late gadolinium enhancement” and “carotid ultrasound”.ConclusionsAI 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. |
| first_indexed | 2024-03-08T00:22:18Z |
| format | Article |
| id | doaj.art-cd7f7854e26b493b84129fc47b8b357e |
| institution | Directory Open Access Journal |
| issn | 2297-055X |
| language | English |
| last_indexed | 2024-03-08T00:22:18Z |
| publishDate | 2024-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cardiovascular Medicine |
| spelling | doaj.art-cd7f7854e26b493b84129fc47b8b357e2024-02-16T05:00:31ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2024-02-011110.3389/fcvm.2024.13239181323918Artificial intelligence applied in cardiovascular disease: a bibliometric and visual analysisJirong Zhang0Jimei Zhang1Juan Jin2Xicheng Jiang3Linlin Yang4Shiqi Fan5Qiao Zhang6Ming Chi7Graduate School, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, ChinaCollege of Public Health, The University of Sydney, NSW, Sydney, AustraliaThe First Department of Cardiovascular, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, HL, ChinaCollege of basic medicine, Heilongjiang University of Chinese Medicine, Harbin, HL, ChinaCardiovascular Disease Branch, Dalian Second People's Hospital, Dalian, LN, ChinaHarbin hospital of traditional Chinese medicine, Harbin, HL, ChinaSchool of Pharmacy, Harbin University of Commerce, Harbin, HL, ChinaGraduate School, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, ChinaBackgroundWith 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.ObjectiveThis 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.MethodsThe 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.ResultsA 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. Circulation is the journal with the largest number of publications in this field. The most important keywords are “classification”, “diagnosis”, and “risk”. Meanwhile, the current research hotpots were “late gadolinium enhancement” and “carotid ultrasound”.ConclusionsAI 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.https://www.frontiersin.org/articles/10.3389/fcvm.2024.1323918/fullcardiovascular diseaseartificial intelligencelate gadolinium enhancementLeft Ventricle Ejection Fraction (LVEF)bibliometric |
| spellingShingle | Jirong Zhang Jimei Zhang Juan Jin Xicheng Jiang Linlin Yang Shiqi Fan Qiao Zhang Ming Chi Artificial intelligence applied in cardiovascular disease: a bibliometric and visual analysis Frontiers in Cardiovascular Medicine cardiovascular disease artificial intelligence late gadolinium enhancement Left Ventricle Ejection Fraction (LVEF) bibliometric |
| title | Artificial intelligence applied in cardiovascular disease: a bibliometric and visual analysis |
| title_full | Artificial intelligence applied in cardiovascular disease: a bibliometric and visual analysis |
| title_fullStr | Artificial intelligence applied in cardiovascular disease: a bibliometric and visual analysis |
| title_full_unstemmed | Artificial intelligence applied in cardiovascular disease: a bibliometric and visual analysis |
| title_short | Artificial intelligence applied in cardiovascular disease: a bibliometric and visual analysis |
| title_sort | artificial intelligence applied in cardiovascular disease a bibliometric and visual analysis |
| topic | cardiovascular disease artificial intelligence late gadolinium enhancement Left Ventricle Ejection Fraction (LVEF) bibliometric |
| url | https://www.frontiersin.org/articles/10.3389/fcvm.2024.1323918/full |
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