医疗保健领域的机器学习和人机信任:系统调查

IF 8.4 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Han Lin, Jiatong Han, Pingping Wu, Jiangyan Wang, Juan Tu, Hao Tang, Liuning Zhu
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引用次数: 0

摘要

随着医疗保健领域人机交互(HMI)的不断发展,人们提出并探讨了医疗保健领域人机交互的信任问题。人类对医疗机器的适当信任对于医疗保健的发展和安全至关重要。应用了机器学习(ML)技术的智能机器不断深入医疗环境,这也对智能医疗提出了更高的要求。为了让机器更有效地在医疗领域的人机界面中发挥作用,让人机合作更加和谐,作者需要在医疗领域建立良好的人机信任(HMT)。本文系统地概述了有关医疗保健中的 ML 和 HMT 的著名研究。此外,本研究还探讨和分析了 ML 以及影响医疗保健领域 HMT 的三个重要因素,然后提出了医疗保健领域的 HMT 模型。最后,本文总结了总体趋势,并指出了未来医疗保健领域 HMT 研究中需要考虑解决的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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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来源期刊
CAAI Transactions on Intelligence Technology
CAAI Transactions on Intelligence Technology COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
11.00
自引率
3.90%
发文量
134
审稿时长
35 weeks
期刊介绍: CAAI Transactions on Intelligence Technology is a leading venue for original research on the theoretical and experimental aspects of artificial intelligence technology. We are a fully open access journal co-published by the Institution of Engineering and Technology (IET) and the Chinese Association for Artificial Intelligence (CAAI) providing research which is openly accessible to read and share worldwide.
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