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人工智能可以通过神经外科的欧洲委员会书面考试吗? - 伦理和实际问题

Felix C Stengel¹, Martin N Stienen¹, Marcel Ivanov²

¹Department of Neurosurgery & Spine Center of Eastern Switzerland, Kantonsspital St. Gallen & Medical School of St.Gallen, St. Gallen, Switzerland.

|March 21, 2024

概括

人工智能 (AI) 大型语言模型 (LLM) 在医学教育中显示出巨大的潜力,在欧洲神经外科协会 (EANS) 董事会的书面考试中,其准确性与人类的表现相当或超过. 这些先进的AI模型在基于文本和基于理论的问题上表现出特别强的优势.

科学领域:

医疗教育中的人工智能
神经外科培训和评估

背景情况:

大型语言模型 (LLM) 在教育中表现有前途,最近的研究表明它们在医学检查中表现优于人类参与者的能力.
欧洲神经外科协会 (EANS) 董事会考试是神经外科学员的关键评估.

研究的目的:

为了评估人工智能 (AI) 在回答EANS董事会考试的书面部分的准确性.
在标准化的神经外科知识评估中,将AI性能与人类参与者进行比较.

主要方法:

考试委员会从以前的EANS董事会考试中选择了86个代表性的单一最佳答案 (SBA) 问题.
将问题分类为基于文本 (TB) 和基于图像 (IB) 的格式,并按结构分类 (解释加权,基于理论,真假).
测试人工智能模型 (Chat GPT 3.5,Bing,Bard) 并使用ANOVA对结果进行统计分析,比较人工智能和人类的性能.

主要成果:

巴德法学士取得了最高的整体准确性 (62%),在书面EANS考试中表现优于人类参与者 (59%).
所有测试的LLM在基于理论的问题上都表现出卓越的表现,明显超过了人类参与者 (例如,Bard: 86%与60%).
人工智能模型无法正确回答任何基于图像的问题,突出显示视觉解释的局限性.

结论:

人工智能,特别是LLM,有能力通过书面EANS董事会考试,取得与人类候选人相当或比人类更好的结果.
这些发现表明,需要根据人工智能的进步重新评估书面EANS董事会考试的当前格式和伦理考虑.
需要进一步的研究来解决AI的局限性,特别是基于图像的评估,并探索AI在神经外科培训中的整合.

关键词:

人工智能的人工智能是人工智能.巴尔德巴尔德巴尔德巴尔德是什么意思这就是为什么BingBingBingBingBing.董事会认证委员会认证在聊天 gpt gpt.埃恩斯埃恩斯是一个人.神经外科的考试委员会.

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