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七个大语言模型在解剖学考试问题上的表现

Weronika Chaba-Karnaś¹, Natalia Kozioł¹, Natalia Kalita¹

¹Department of Anatomy, Jagiellonian University Medical College, Kraków, Poland.

Clinical anatomy (New York, N.Y.)

|January 10, 2026

概括

人工智能 (AI) 模型在解决医学解剖学考试方面表现出很高的效率,表现最好的模型的准确率超过80%. 这种能力引起了教育工作者对学生评估和学术完整性的担忧,因为人工智能技术在不断发展.

科学领域:

医疗教育医学教育
人工智能的人工智能
人体解剖学解剖学解剖学

背景情况:

人工智能 (AI) 和大型语言模型 (LLM) 的快速发展需要评估它们在医学等专业领域的实用性.
人工智能对医学教育的潜在影响,特别是在解剖学评估中,需要进行彻底的调查.

研究的目的:

评估各种AI语言模型在回答专为医学学生设计的理论解剖学考试问题的有效性.
将人工智能性能与人类学生在解剖学知识方面的能力进行基准测试.

主要方法:

从过去的医学学生考试中利用了555个多选择解剖学问题 (150个波兰语,405个英语).
测试了七个人工智能模型:ChatGPT-4o mini,ChatGPT-4o,DeepSeek,Copilot,Gemini,Bielik和PLLum. 这些都是我们测试的.
分析基于问题类型和解剖学主题的AI性能.

主要成果:

聊天GPT-4o获得了最高的准确度 (83.1%),其次是Copilot (79.6%) 和Gemini (78.8%).
人工智能模型通常在有关器官功能的问题上表现更好 (75%),在多个答案问题上表现更差 (37.6%).
大多数经过测试的AI模型都证明了能够独立通过解剖学考试的能力.

结论:

目前的AI语言模型在回答解剖学考试问题方面具有显著的能力,可能超过人类学生的通过率.
教师必须调整评估策略以考虑AI能力,因为AI性能正在迅速提高.
开发抗人工智能评估方法对于保持医学教育学术完整性至关重要.

关键词:

人体解剖学解剖学解剖学解剖学教学教学解剖学教学人工智能的人工智能是人工智能.大型语言模型.测试测试测试测试测试

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