Information fusion and artificial intelligence for smart healthcare: a bibliometric study. Issue 1 (January 2023)

• Record Type: Journal Article
• Authors: Chen, Xieling; Xie, Haoran; Li, Zongxi; Cheng, Gary; Leng, Mingming; Wang, Fu Lee
• Is Part Of: Information processing & management. Volume 60:Issue 1(2023)
• Publication Date: 2023-01
• Subjects: Information fusion -- Artificial intelligence -- Smart healthcare -- Structural topic modeling -- Bibliometrics -- Topic evolution; Information storage and retrieval systems -- Periodicals; Information science -- Periodicals; Systèmes d'information -- Périodiques; Sciences de l'information -- Périodiques; Information science; Information storage and retrieval systems; Periodicals; 658.4038
• DOI: 10.1016/j.ipm.2022.103113
• Languages: English
• ISSNs: 0306-4573

Abstract

Highlights: Focus on information fusion for smart health with artificial intelligence. Conduct a structural topic model-based bibliometric analysis. Identify major contributors and visualize the scientific collaborations. Identify predominant research topics and potential future directions. Visualize topical distributions of major contributors. Abstract: 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.