Dataset Information

Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study.

ABSTRACT: The increasing application of Artificial Intelligence (AI) in health and medicine has attracted a great deal of research interest in recent decades. This study aims to provide a global and historical picture of research concerning AI in health and medicine. A total of 27,451 papers that were published between 1977 and 2018 (84.6% were dated 2008?2018) were retrieved from the Web of Science platform. The descriptive analysis examined the publication volume, and authors and countries collaboration. A global network of authors' keywords and content analysis of related scientific literature highlighted major techniques, including Robotic, Machine learning, Artificial neural network, Artificial intelligence, Natural language process, and their most frequent applications in Clinical Prediction and Treatment. The number of cancer-related publications was the highest, followed by Heart Diseases and Stroke, Vision impairment, Alzheimer's, and Depression. Moreover, the shortage in the research of AI application to some high burden diseases suggests future directions in AI research. This study offers a first and comprehensive picture of the global efforts directed towards this increasingly important and prolific field of research and suggests the development of global and national protocols and regulations on the justification and adaptation of medical AI products.

SUBMITTER: Tran BX

PROVIDER: S-EPMC6463262 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study.

Tran Bach Xuan BX Tran Bach Xuan BX Vu Giang Thu GT Ha Giang Hai GH Vuong Quan-Hoang QH Ho Manh-Tung MT Vuong Thu-Trang TT La Viet-Phuong VP Ho Manh-Toan MT Nghiem Kien-Cuong P KP Nguyen Huong Lan Thi HLT Latkin Carl A CA Tam Wilson W S WWS Cheung Ngai-Man NM Nguyen Hong-Kong T HT Ho Cyrus S H CSH Ho Roger C M RCM

Journal of clinical medicine 20190314 3

The increasing application of Artificial Intelligence (AI) in health and medicine has attracted a great deal of research interest in recent decades. This study aims to provide a global and historical picture of research concerning AI in health and medicine. A total of 27,451 papers that were published between 1977 and 2018 (84.6% were dated 2008⁻2018) were retrieved from the Web of Science platform. The descriptive analysis examined the publication volume, and authors and countries collaboration ...[more]

PMID: 30875745

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Project description:BackgroundImmunosenescence, an age-related deficit in immunity, associated with multiple disorders and making the successful aging a challenge. Although nearly 4000 articles have been published, only few review articles have summarized the research status. In order to better understand the most recent advances, hotspots and development trends in immunosenescence, it is very necessary to conduct a comprehensive bibliometric analysis. Hence, commonly used bibliometric analysis software CiteSpace and VOSviewer were employed to conduct a quantitative analysis and critical evaluation of publications in this study.MethodsImmunosenescence publications were screened from the Web of Science Core Collection (WoSCC). Microsoft Excel 2021, CiteSpace 5.8.R3, and VOSviewer 1.6.17 were used for bibliometric study.ResultsA total of 3875 publications were retrieved from WoSCC. After screening by document type (article or review) (352 publications were excluded) and language of English (85 were excluded), 3438 studies were finally used for bibliometric analysis. The literature on immunosenescence had been continuously growing since 1991, and by 2020 it has skyrocketed 312 publications from 240 in 2019. USA (1111 publications, 35.01%) was the leading country of publications, followed by ITALY (379, 11.94%) and ENGLAND (366, 11.53%). Of the authors, Pawelec G from the Tubingen University of GERMANY contributed the greatest articles (93 publications). All the keywords could be divided into five clusters, and additional potent visualization bursts revealed that "gut microbiota," "health," "dysfunction," and "nivolumab" were the active hotspots presently.ConclusionBased on the current data, we firstly concluded that there will be a dramatically rising publications on immunosenescence, and research teams from USA or GERMANY might be the best chooses for collaboration. Moreover, We particularly emphasized the development potential of mechanism and intervening strateges like "gut microbiota" and "nivolumab" in immunosenescence. We hope to provide new ideas for promoting the basic research and clinical application of immunosenescence.

Dataset Information

Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study.

Publications

Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study.

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