CAAI Transactions on Intelligence Technology (Apr 2024)

Machine learning and human‐machine trust in healthcare: A systematic survey

  • Han Lin,
  • Jiatong Han,
  • Pingping Wu,
  • Jiangyan Wang,
  • Juan Tu,
  • Hao Tang,
  • Liuning Zhu

DOI
https://doi.org/10.1049/cit2.12268
Journal volume & issue
Vol. 9, no. 2
pp. 286 – 302

Abstract

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Abstract As human‐machine interaction (HMI) in healthcare continues to evolve, the issue of trust in HMI in healthcare has been raised and explored. It is critical for the development and safety of healthcare that humans have proper trust in medical machines. Intelligent machines that have applied machine learning (ML) technologies continue to penetrate deeper into the medical environment, which also places higher demands on intelligent healthcare. In order to make machines play a role in HMI in healthcare more effectively and make human‐machine cooperation more harmonious, the authors need to build good human‐machine trust (HMT) in healthcare. This article provides a systematic overview of the prominent research on ML and HMT in healthcare. In addition, this study explores and analyses ML and three important factors that influence HMT in healthcare, and then proposes a HMT model in healthcare. Finally, general trends are summarised and issues to consider addressing in future research on HMT in healthcare are identified.

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