4.7 Article

Information fusion and artificial intelligence for smart healthcare: a bibliometric study

Journal

INFORMATION PROCESSING & MANAGEMENT
Volume 60, Issue 1, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.ipm.2022.103113

Keywords

Information fusion; Artificial intelligence; Smart healthcare; Structural topic modeling; Bibliometrics; Topic evolution

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With the rapid development of information technologies and artificial intelligence, smart healthcare and the integration of various healthcare data have gained significant momentum. This study provides a comprehensive analysis of information fusion for healthcare with AI, including major research topics, trends, and correlations, as well as the primary concerns of top countries/regions, institutions, and authors. The findings offer valuable insights for the future development of smart health with AI and guidance for international collaborations.
With the fast progress in information technologies and artificial intelligence (AI), smart healthcare has gained considerable momentum. By using advanced technologies like AI, smart healthcare aims to promote human beings' health and well-being throughout their life. As smart healthcare develops, big healthcare data are produced by various sensors, devices, and communication technologies constantly. To deal with these big multi-source data, automatic information fusion becomes crucial. Information fusion refers to the integration of multiple information sources for obtaining more reliable, effective, and precise information to support optimal decision-making. The close study of information fusion for healthcare with the adoption of advanced AI technologies has become an increasingly important and active field of research. The aim of this is to present a systematic description and state-of-the-art understanding of research about information fusion for healthcare with AI. Structural topic modeling was implemented to detect major research topics covered within 351 relevant articles. Annual trends and correlations of the identified topics were also investigated to identify potential future research directions. In addition, the primary research concerns of top countries/regions, institutions, and authors were shown and compared. The findings based on our analyses provide scientific and technological perspectives of research on information fusion for smart health with AI and offer useful insights and implications for its future development. We also provide valuable guidance for researchers and project managers to allocate research resources and promote effective international collaborations.

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