对比大型语言模型的牙科知识.
Camila Tussie1, Abraham Starosta2
1Harvard School of Dental Medicine, Boston, Massachusetts, USA. camitussie@hsdm.harvard.edu.
British dental journal
|November 1, 2024
概括
聊天GPT-4在测试的大型语言模型 (LLM) 中表现出卓越的牙科知识,在综合国家委员会牙科考试问题上获得75.88%的准确性. 这凸显了LLM选择牙科应用的重要性.
科学领域:
- 人工智能在牙科中的应用
- 自然语言处理应用程序
背景情况:
- 大型语言模型 (LLM) 提供了人工智能在牙科整合的潜力,影响了临床实践,管理和教育.
- 在LLMs中获得准确的牙科知识对于减轻患者护理和教育中的风险至关重要.
研究的目的:
- 为了比较不同LLM的牙科知识准确度.
- 为了评估LLM在综合国家委员会牙科考试 (INBDE) 问题上的表现.
主要方法:
- 评估了闭源和开源的LLMs.
- 分析了INBDE患者框和多选题的答案.
主要成果:
- 聊天GPT-4获得了最高的准确性 (75.88%),其次是克劳德-2.1 (66.38%) 和米斯特拉尔-中等 (54.77%).
- 在所有评估的LLMs中观察到具有统计意义的绩效差异.
结论:
- 士课程显示出牙科领域整合的巨大潜力.
- 精心选择LLMs对于开发可靠的牙科技术至关重要.
- 在未经监督的临床部署LLMs之前,限制需要解决.
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