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对医学人工智能革命的期望调适:医学实习生的观点

Tempering Expectations on the Medical Artificial Intelligence Revolution: The Medical Trainee Viewpoint.

作者信息

Hu Zoe, Hu Ricky, Yau Olivia, Teng Minnie, Wang Patrick, Hu Grace, Singla Rohit

机构信息

School of Medicine, Queen's University, Kingston, ON, Canada.

School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada.

出版信息

JMIR Med Inform. 2022 Aug 15;10(8):e34304. doi: 10.2196/34304.

Abstract

The rapid development of artificial intelligence (AI) in medicine has resulted in an increased number of applications deployed in clinical trials. AI tools have been developed with goals of improving diagnostic accuracy, workflow efficiency through automation, and discovery of novel features in clinical data. There is subsequent concern on the role of AI in replacing existing tasks traditionally entrusted to physicians. This has implications for medical trainees who may make decisions based on the perception of how disruptive AI may be to their future career. This commentary discusses current barriers to AI adoption to moderate concerns of the role of AI in the clinical setting, particularly as a standalone tool that replaces physicians. Technical limitations of AI include generalizability of performance and deficits in existing infrastructure to accommodate data, both of which are less obvious in pilot studies, where high performance is achieved in a controlled data processing environment. Economic limitations include rigorous regulatory requirements to deploy medical devices safely, particularly if AI is to replace human decision-making. Ethical guidelines are also required in the event of dysfunction to identify responsibility of the developer of the tool, health care authority, and patient. The consequences are apparent when identifying the scope of existing AI tools, most of which aim to be physician assisting rather than a physician replacement. The combination of the limitations will delay the onset of ubiquitous AI tools that perform standalone clinical tasks. The role of the physician likely remains paramount to clinical decision-making in the near future.

摘要

人工智能(AI)在医学领域的迅速发展导致了越来越多的应用被部署到临床试验中。开发人工智能工具的目标是提高诊断准确性、通过自动化提高工作流程效率以及发现临床数据中的新特征。随后人们担心人工智能在取代传统上由医生承担的现有任务方面所起的作用。这对医学实习生有影响,他们可能会基于对人工智能对其未来职业可能造成的干扰程度的认知来做出决策。本评论讨论了当前人工智能应用面临的障碍,以缓解人们对人工智能在临床环境中作用的担忧,特别是作为取代医生的独立工具的作用。人工智能的技术局限性包括性能的可推广性以及现有基础设施在容纳数据方面的不足,这两点在试点研究中不太明显,因为在试点研究中,在受控的数据处理环境中能实现高性能。经济局限性包括安全部署医疗设备的严格监管要求,特别是如果人工智能要取代人类决策的话。如果出现功能失调情况,还需要道德准则来确定工具开发者、医疗保健机构和患者的责任。在确定现有人工智能工具的范围时,后果很明显,其中大多数旨在辅助医生而非取代医生。这些局限性的综合作用将推迟能执行独立临床任务的普及型人工智能工具的出现。在不久的将来,医生在临床决策中的作用可能仍然至关重要。

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