大型语言模型在化物相关的牙科知识中的表现:ChatGPT-4,Claude 3.5 Sonnet,Copilot和Grok 3的比较评估研究
Raju Biswas1, Atanu Mukhopadhyay2, Santanu Mukhopadhyay3
1Department of Pediatric and Preventive Dentistry, Dr R Ahmed Dental College and Hospital, Kolkata, India.
Journal of Yeungnam medical science
|September 2, 2025
概括
四个先进的大型语言模型 (LLM) 在牙科教育方面表现出色,克劳德3.5索内特在化物相关主题的清晰度方面表现出色. 这些人工智能工具有助于改善牙科培训和患者沟通.
科学领域:
- 教育中的人工智能
- 牙科科学与技术
- 自然语言处理应用
背景情况:
- 大型语言模型 (LLM) 在医学和牙科教育中越来越多地用于临床推理和沟通.
- 需要严格评估LLM在牙科专业知识中的有效性,特别是关于化物.
- 这项研究评估了四个主要的LLM:ChatGPT-4,Claude 3.5 Sonnet,微软Copilot和Grok 3.
研究的目的:
- 评估先进的大型语言模型 (LLM) 在传递化物相关的专业牙科知识方面的表现.
- 在准确性,深度,清晰度和证据方面比较ChatGPT-4,Claude 3.5 Sonnet,微软Copilot和Grok 3.
- 确定LLM作为补充牙科教育工具的潜力.
主要方法:
- 一个横截面的比较分析使用混合方法框架.
- 每个LLM都对化物化学,应用和安全进行了50个多选题和10个开放式问题.
- 专家评价者使用标题评估开放式答复;统计分析比较了LLM的表现.
主要成果:
- 所有评估的LLM在多选题中都表现出很高的准确性 (88%-94%).
- 克劳德 3.5 索内特在开放式答案的清晰度方面取得了统计学上的优异成绩 (p=0.009).
- 虽然在准确度,深度和证据方面存在小差异,但所有LLM在传递含量方面都表现出色.
结论:
- 先进的LLM具有重要的潜力作为牙科教育和有关的患者沟通的补充工具.
- 克劳德 3.5 索内特在语言清晰度方面具有明显的优势,使其对教育应用特别有价值.
- 持续评估,临床验证和监督对于LLM在牙科安全有效的整合至关重要.
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