人工智能在放射学中的应用:患者视角的叙述性综述

The implementation of artificial intelligence in radiology: a narrative review of patient perspectives.

作者信息

Hemphill Scott, Jackson Katherine, Bradley Stephen, Bhartia Bobby

机构信息

Sir Charles Gairdner Hospital, Perth, Australia.

Leeds Institute of Health Sciences, University of Leeds, Leeds, UK.

出版信息

Future Healthc J. 2023 Mar;10(1):63-68. doi: 10.7861/fhj.2022-0097.

Abstract

AIM

To synthesise research on the view of the public and patients of the use of artificial intelligence (AI) in radiology investigations.

METHODS

A literature review of narrative synthesis of qualitative and quantitative studies that reported views of the public and patients toward the use of AI in radiology.

RESULTS

Only seven studies related to patient and public views were retrieved, suggesting that this is an underexplored area of research. Two broad themes, of confidence in the capabilities of AI, and the accountability and transparency of AI, were identified.

CONCLUSIONS

Both optimism and concerns were expressed by participants. Transparency in the implementation of AI, scientific validation, clear regulation and accountability were expected. Combined human and AI interpretation of imaging was strongly favoured over AI acting autonomously. The review highlights the limited engagement of the public in the adoption of AI in a radiology setting. Successful implementation of AI in this field will require demonstrating not only adequate accuracy of the technology, but also its acceptance by patients.

摘要

目的

综合关于公众和患者对人工智能(AI)在放射学检查中应用看法的研究。

方法

对定性和定量研究的叙述性综合进行文献综述,这些研究报告了公众和患者对AI在放射学中应用的看法。

结果

仅检索到七项与患者和公众观点相关的研究,表明这是一个研究不足的领域。确定了两个广泛的主题,即对AI能力的信心以及AI的问责制和透明度。

结论

参与者表达了乐观和担忧。期望AI实施过程中的透明度、科学验证、明确的监管和问责制。强烈支持人类与AI联合解读影像,而不是AI自主操作。该综述强调了公众在放射学环境中采用AI方面的参与有限。要在该领域成功实施AI,不仅需要证明该技术具有足够的准确性,还需要证明患者对其的接受程度。

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