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评估GPT-4在紧急情况下的视觉解释和临床推理:五年分析分析

Te-Hao Wang¹, Jing-Cheng Jheng¹, Yen-Ting Tseng¹

¹Department of Emergency Medicine, National Yang Ming Chiao Tung University Hospital, I-Lan, Taiwan, ROC.

Journal of the Chinese Medical Association : JCMA

|July 28, 2025

概括

像GPT-4这样的生成人工智能显示出强大的图像识别能力,但在紧急医疗检查中难以做出临床决策. 为了可靠的医疗应用,需要进一步开发人工智能.

科学领域:

人工智能在医学中的应用
医疗教育技术技术医学教育
紧急医疗诊断诊断诊断诊断

背景情况:

生成型人工智能,特别是像GPT-4这样的大型语言模型 (LLM),在医学教育中越来越多地被使用.
本研究评估了GPT-4在解释紧急医疗委员会考试问题方面的表现,包括基于文本和图像的格式.

研究的目的:

在模拟紧急医疗场景中评估GPT-4的认知和决策能力.
为了确定GPT-4的准确性和推理能力在董事会考试问题上.

主要方法:

一项观察性研究利用了2018-2022年台湾紧急医疗委员会考试问题.
分析了GPT-4在不同类型问题中的准确性和推理性.
统计分析探讨了影响绩效的因素,如知识维度和认知水平.

主要成果:

GPT-4的整体准确率达到60.1%,在基于文本 (60.2%) 和基于图像 (59.3%) 的问题上表现相似.
在图像识别 (100%) 和解释 (86.4%) 中观察到高精度,但在诊断推理 (83.1%) 和决策 (59.3%) 中下降.
在问题特征和GPT-4的表现之间没有发现显著的关联.

结论:

GPT-4表现出强大的图像识别和中度的诊断推理,但有限的临床决策,特别是在整合视觉和临床数据时.
虽然GPT-4作为一个教育工具是有前途的,但GPT-4目前的依赖于模式识别而不是临床理解限制了其在紧急医疗中的实际应用.
人工智能需要进一步的进步,以可靠地支持紧急医疗决策.

关键词:

紧急医疗委员会考试在GPT-4模型中.生成性AI是一种人工智能.视觉识别性能表现的表现

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