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一种用于医学人工智能包络的基于信任的框架。

A trust based framework for the envelopment of medical AI.

作者信息

Zuchowski Lena Christine, Zuchowski Matthias Lukas, Nagel Eckhard

机构信息

University of Bristol, Department of Philosophy, Cotham House, Bristol, BS6 6JL, UK.

Robert Bosch Hospital, Auerbachstr. 110, 70376, Stuttgart, Germany.

出版信息

NPJ Digit Med. 2024 Aug 27;7(1):230. doi: 10.1038/s41746-024-01224-3.

DOI:10.1038/s41746-024-01224-3
PMID:39191927
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11350073/
Abstract

The importance of a trust-based relationship between patients and medical professionals has been recognized as one of the most important predictors of treatment success and patients' satisfaction. We have developed a novel legal, social and regulatory envelopment of medical AI that is explicitly based on the preservation of trust between patients and medical professionals. We require that the envelopment fosters reliance on the medical AI by both patients and medical professionals. Focusing on this triangle of desirable attitudes allows us to develop eight envelopment components that will support, strengthen and preserve these attitudes. We then demonstrate how each envelopment component can be enacted during different stages of the systems development life cycle and demonstrate that this requires the involvement of medical professionals and patients at the earliest stages of the life cycle. Therefore, this framework requires medical AI start-ups to cooperate with medical professionals and patients throughout.

摘要

患者与医疗专业人员之间基于信任的关系的重要性,已被视为治疗成功和患者满意度的最重要预测因素之一。我们开发了一种全新的医疗人工智能的法律、社会和监管环境,该环境明确基于维护患者与医疗专业人员之间的信任。我们要求这种环境促进患者和医疗专业人员对医疗人工智能的信赖。关注这一理想态度的三角关系,使我们能够开发出八个环境组成部分,以支持、强化和维护这些态度。然后,我们展示了每个环境组成部分如何在系统开发生命周期的不同阶段得以实施,并表明这需要医疗专业人员和患者在生命周期的最早阶段参与进来。因此,这个框架要求医疗人工智能初创企业自始至终与医疗专业人员和患者合作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4c/11350073/530fd11ccf12/41746_2024_1224_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4c/11350073/17b6a83ee09d/41746_2024_1224_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4c/11350073/530fd11ccf12/41746_2024_1224_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4c/11350073/17b6a83ee09d/41746_2024_1224_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4c/11350073/530fd11ccf12/41746_2024_1224_Fig2_HTML.jpg

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本文引用的文献

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The impact of artificial intelligence on the person-centred, doctor-patient relationship: some problems and solutions.人工智能对以患者为中心、医患关系的影响:一些问题及解决方案。
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Transparency of AI in Healthcare as a Multilayered System of Accountabilities: Between Legal Requirements and Technical Limitations.作为多层问责制系统的医疗保健领域人工智能的透明度:介于法律要求与技术限制之间
Front Artif Intell. 2022 May 30;5:879603. doi: 10.3389/frai.2022.879603. eCollection 2022.
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糖尿病神经病变:前沿研究与未来方向
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The ethics of AI in health care: A mapping review.医疗保健领域人工智能的伦理问题:一项映射性综述。
Soc Sci Med. 2020 Sep;260:113172. doi: 10.1016/j.socscimed.2020.113172. Epub 2020 Jul 15.
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Learn Health Syst. 2019 Dec 4;4(2):e10206. doi: 10.1002/lrh2.10206. eCollection 2020 Apr.
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