在神经瘤学中评估大型语言模型:对准确性,完整性和临床有用性的比较研究
Shefqet Hajdari1, Minaam Farooq2, Aleeza Habib2
1University Hospital Bonn, Department of Neurosurgery, Bonn, Germany.
概括
与Gemini Advanced和ChatGPT-3. 5相比,ChatGPT-4在神经瘤病例的准确性,完整性和有用性方面表现出更好的表现. 建议在临床实践中进一步研究大型语言模型 (LLM).
科学领域:
- 医学的人工智能
- 临床决策支持系统
- 神经瘤学研究
背景情况:
- 由于其数据处理能力,大型语言模型 (LLM) 越来越多地被用于医疗保健应用.
- 评估LLM在神经瘤学等专业领域的临床效用至关重要.
- 目前在复杂的医学领域的LLM需要严格的评估.
研究的目的:
- 在神经瘤学中比较Gemini Advanced,ChatGPT-3.5和ChatGPT-4反应的准确性,完整性和有用性.
- 在神经瘤病例管理的各个方面评估LLM的表现.
- 确定最有效的神经瘤学临床决策支持的LLM.
主要方法:
- 这项研究使用了20个常见的神经瘤病例.
- 对每个LLM提出了四个标准问题 (差异诊断,工作,临时诊断,管理).
- 高级神经瘤学家使用准确性,完整性和有用性等级来评估反应,并使用统计分析 (ANOVA,Dunn的测试).
主要成果:
- 聊天GPT-4在准确性 (x̅=5.12),完整性 (x̅=2.05) 和有用性 (x̅=2.06) 方面获得最高分.
- 双子先进显示了类似的性能,其次是ChatGPT-3.
- 在差异诊断的完整性和LLM的整体完整性方面观察到有统计学意义的差异.
结论:
- 在被测试者中,ChatGPT-4似乎是最熟练的神经瘤病例评估LLM.
- 需要更多的神经外科医生和多种病例进行进一步的广泛研究,
- 未来的研究可以通过专门的神经瘤学培训来研究恢复增强生成 (RAG).
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