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赋能早期职业神经外科医生进行人工智能和机器学习的批判性评估:一项试点课程的设计与评估。

Empowering Early Career Neurosurgeons in the Critical Appraisal of Artificial Intelligence and Machine Learning: The Design and Evaluation of a Pilot Course.

机构信息

UCL Medical School, University College London, London, United Kingdom.

Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom; Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom.

出版信息

World Neurosurg. 2024 Oct;190:e537-e547. doi: 10.1016/j.wneu.2024.07.166. Epub 2024 Jul 27.


DOI:10.1016/j.wneu.2024.07.166
PMID:39074581
Abstract

BACKGROUND: Artificial intelligence (AI) is expected to play a greater role in neurosurgery. There is a need for neurosurgeons capable of critically appraising AI literature to evaluate its implementation or communicate information to patients. However, there are a lack of courses delivered at a level appropriate for individuals to develop such skills. We assessed the impact of a 2-day (non-credit bearing) online digital literacy course on the ability of individuals to critically appraise AI literature in neurosurgery. METHODS: We performed a prospective, quasi-experimental non-randomized, controlled study with an intervention arm comprising individuals enrolled in our 2-day digital health literacy course and a waiting-list control arm used for comparison. We assessed participants' pre- and post-course knowledge, confidence, and course acceptability using Qualtrics surveys designed for the purpose of this study. RESULTS: A total of 62 individuals (33 participants, 29 waitlist controls), including neurosurgical trainees and both undergraduate and post-graduate students, attended the course and completed the pre-course survey. The 2 groups did not vary significantly in terms of age or demographics. Following the course, participants significantly improved in their knowledge of AI (mean difference = 3.86, 95% CI = 2.97-4.75, P-value < 0.0001) and confidence in critically appraising literature using AI (P-value = 0.002). Similar differences in knowledge (mean difference = 3.15, 95% CI = 1.82-4.47, P-value < 0.0001) and confidence (P-value < 0.0001) were found when compared to the control group. CONCLUSIONS: Bespoke courses delivered at an appropriate level can improve clinicians' understanding of the application of AI in neurosurgery, without the need for in-depth technical knowledge or programming skills.

摘要

背景:人工智能(AI)有望在神经外科中发挥更大的作用。神经外科医生需要具备批判性评估 AI 文献的能力,以评估其实施情况或向患者传达信息。然而,目前缺乏适合个人发展此类技能的课程。我们评估了为期 2 天(无学分)的在线数字素养课程对个人批判性评估神经外科 AI 文献能力的影响。

方法:我们进行了一项前瞻性、准实验性、非随机、对照研究,干预组包括参加我们 2 天数字健康素养课程的个人和用于比较的候补名单对照组。我们使用专门为此研究设计的 Qualtrics 调查评估了参与者在课程前后的知识、信心和课程接受度。

结果:共有 62 人(33 名参与者,29 名候补名单对照组)参加了课程并完成了预课程调查,包括神经外科受训者以及本科和研究生学生。这两组在年龄或人口统计学方面没有显著差异。在课程结束后,参与者在 AI 知识方面有显著提高(平均差异=3.86,95%置信区间=2.97-4.75,P 值<0.0001),并对使用 AI 批判性评估文献的信心有显著提高(P 值=0.002)。与对照组相比,在知识(平均差异=3.15,95%置信区间=1.82-4.47,P 值<0.0001)和信心(P 值<0.0001)方面也有类似的差异。

结论:专门提供的适合个人水平的课程可以提高临床医生对 AI 在神经外科中应用的理解,而无需深入的技术知识或编程技能。

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