Topics and trends in artificial intelligence assisted human brain research.

Journal: PloS one
Published Date:

Abstract

Artificial intelligence (AI) assisted human brain research is a dynamic interdisciplinary field with great interest, rich literature, and huge diversity. The diversity in research topics and technologies keeps increasing along with the tremendous growth in application scope of AI-assisted human brain research. A comprehensive understanding of this field is necessary to assess research efficacy, (re)allocate research resources, and conduct collaborations. This paper combines the structural topic modeling (STM) with the bibliometric analysis to automatically identify prominent research topics from the large-scale, unstructured text of AI-assisted human brain research publications in the past decade. Analyses on topical trends, correlations, and clusters reveal distinct developmental trends of these topics, promising research orientations, and diverse topical distributions in influential countries/regions and research institutes. These findings help better understand scientific and technological AI-assisted human brain research, provide insightful guidance for resource (re)allocation, and promote effective international collaborations.

Authors

  • Xieling Chen
    College of Economics, Jinan University, Guangzhou, China.
  • Juan Chen
    Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China. chenjuan94@bjmu.edu.cn.
  • Gary Cheng
    Department of Mathematics and Information Technology, The Education University of Hong Kong, Hong Kong SAR, China.
  • Tao Gong
    Educational Testing Service, Princeton, NJ, USA.