大型语言模型与临床医生和兽医神经遗传学新手之间的性能支持决策
Damla Tuğçe Okur1, Mehmet Cengiz2, İbrahim Küçükaslan3
11Department of Obstetrics and Gynecology, Faculty of Veterinary Medicine, Atatürk University, Erzurum, Turkey.
Journal of the American Veterinary Medical Association
|February 14, 2026
概括
像ChatGPT-5 Thinking这样的大型语言模型 (LLM) 在兽医神经遗传学方面表现有前途,提供与专家临床医生竞争的临床决策支持,并在模拟场景中超越新手.
科学领域:
- 兽医医学 兽医医学 兽医医学
- 人工智能的人工智能
- 生殖健康 生殖健康
背景情况:
- 临床决策支持在兽医神经遗传学中至关重要.
- 大型语言模型 (LLM) 具有帮助临床决策的潜力.
研究的目的:
- 为了比较两名LLM (ChatGPT-5和ChatGPT-5思维) 的临床决策支持性能,与经验丰富的临床医生和兽医产物学新手进行比较.
主要方法:
- 15个标准化产科和妇科场景被专家临床医生,初学者兽医和两位LLMs评估.
- 通过一个盲目专家小组,通过5分的全球质量评分来评估答案.
主要成果:
- 聊天GPT-5思维获得了最高的质量评级,其次是聊天GPT-5和专家临床医生.
- 总体而言,LLM的反应比人类的反应更一致,更完整.
- 新手兽医的得分最低.
结论:
- 在模拟病例中,LLM,特别是ChatGPT-5思维,提供了临床上适当的指导,超过了新手的表现,接近专家临床医生水平.
- 在兽医中,LLM显示出对时间敏感的妇产科和妇产科病例的辅助决策支持工具的潜力.
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