定制大型语言模型在胃肠病学中的潜在临床实用性:试点研究
Eun Jeong Gong1,2,3, Chang Seok Bang1,2,3, Jae Jun Lee3,4
1Department of Internal Medicine, Hallym University College of Medicine, Chuncheon 24253, Republic of Korea.
Bioengineering (Basel, Switzerland)
|January 24, 2025
概括
大型语言模型 (LLM) 在胃肠病学中表现有前途,GPT-4o的表现优于定制模型. 检索增强生成 (RAG) 是复杂数据的关键,但临床医生监督仍然至关重要.
科学领域:
- 胃肠病学 胃肠病学
- 人工智能的人工智能
- 临床决策支持 临床决策支持
背景情况:
- 大型语言模型 (LLM) 在临床实践中具有潜力,但它们在胃肠病学中的应用尚未得到充分研究.
- 胃肠道学对人工智能提出了独特的挑战,原因是复杂的,专门的信息.
研究的目的:
- 探索定制GPT模型和常规GPT-4o在胃肠病学中的临床实用性.
- 将LLMs的表现与胃肠病学研究员和专家胃肠病学家进行比较.
主要方法:
- 使用BM25和GPT-4o的定制GPT模型是通过内部医学和韩国胃肠道学教科书开发的.
- 为了进行比较,访问了一个常规的ChatGPT 4o.
- 由专家开发的15个临床问题的基准被用来测试LLMs,一个同学和一个专家.
主要成果:
- 定制的LLM正确回答了8/15个问题;它的表现提高了英语术语,但在基于判断的问题上扎.
- 传统的GPT-4o获得了最高的AI分数 (14/15),超过了定制模型和胃肠病学研究员 (10/15).
- 两位LLM的成绩都与同学相当或比他更好,表明了显著的潜力,尽管略低于专家 (15/15).
结论:
- 法律学士可以协助专业任务,如胃肠病学患者咨询.
- 检索增强生成 (RAG) 对于处理复杂的专业医疗数据至关重要.
- 临床医生监督对于安全有效地将LLMs纳入临床实践至关重要.
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