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骨科医生对医学研究中人工智能的接受与理解

Acceptance and understanding of artificial intelligence in medical research among orthopaedic surgeons.

作者信息

Ormond Michael J, Clement Nick D, Harder Ben G, Farrow Luke, Glester Andrew

机构信息

Science Communication Unit, University of the West of England, Bristol, UK.

Stryker Orthopaedics, Mahwah, New Jersey, USA.

出版信息

Bone Jt Open. 2023 Sep 11;4(9):696-703. doi: 10.1302/2633-1462.49.BJO-2023-0070.R1.

Abstract

AIMS

The principles of evidence-based medicine (EBM) are the foundation of modern medical practice. Surgeons are familiar with the commonly used statistical techniques to test hypotheses, summarize findings, and provide answers within a specified range of probability. Based on this knowledge, they are able to critically evaluate research before deciding whether or not to adopt the findings into practice. Recently, there has been an increased use of artificial intelligence (AI) to analyze information and derive findings in orthopaedic research. These techniques use a set of statistical tools that are increasingly complex and may be unfamiliar to the orthopaedic surgeon. It is unclear if this shift towards less familiar techniques is widely accepted in the orthopaedic community. This study aimed to provide an exploration of understanding and acceptance of AI use in research among orthopaedic surgeons.

METHODS

Semi-structured in-depth interviews were carried out on a sample of 12 orthopaedic surgeons. Inductive thematic analysis was used to identify key themes.

RESULTS

The four intersecting themes identified were: 1) validity in traditional research, 2) confusion around the definition of AI, 3) an inability to validate AI research, and 4) cautious optimism about AI research. Underpinning these themes is the notion of a validity heuristic that is strongly rooted in traditional research teaching and embedded in medical and surgical training.

CONCLUSION

Research involving AI sometimes challenges the accepted traditional evidence-based framework. This can give rise to confusion among orthopaedic surgeons, who may be unable to confidently validate findings. In our study, the impact of this was mediated by cautious optimism based on an ingrained validity heuristic that orthopaedic surgeons develop through their medical training. Adding to this, the integration of AI into everyday life works to reduce suspicion and aid acceptance.

摘要

目的

循证医学(EBM)原则是现代医学实践的基础。外科医生熟悉常用的统计技术,用于检验假设、总结研究结果,并在特定概率范围内提供答案。基于这些知识,他们能够在决定是否将研究结果应用于实践之前,对研究进行批判性评估。最近,人工智能(AI)在骨科研究中用于分析信息和得出研究结果的应用有所增加。这些技术使用的一系列统计工具越来越复杂,骨科医生可能并不熟悉。目前尚不清楚这种向不太熟悉的技术的转变在骨科界是否被广泛接受。本研究旨在探讨骨科医生对研究中使用人工智能的理解和接受情况。

方法

对12名骨科医生进行了半结构化深度访谈。采用归纳主题分析法确定关键主题。

结果

确定了四个相互交叉的主题:1)传统研究中的有效性,2)对人工智能定义的困惑,3)无法验证人工智能研究,4)对人工智能研究持谨慎乐观态度。这些主题的基础是有效性启发法的概念,该概念深深植根于传统研究教学,并融入医学和外科培训之中。

结论

涉及人工智能的研究有时会挑战公认的传统循证框架。这可能会在骨科医生中引起困惑,他们可能无法自信地验证研究结果。在我们的研究中,这种影响通过基于骨科医生在医学培训中形成的根深蒂固的有效性启发法的谨慎乐观态度得到调节。此外,人工智能融入日常生活有助于减少怀疑并促进接受。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f755/10494473/701e3cc42a4b/BJO-2023-0070.R1-galleyfig1.jpg

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