大型语言模型驱动的聊天机器人的性能与瘤学医生在结直肠癌查询中的表现相比
Shan Zhou1, Xiao Luo2, Chan Chen3
1Florida Research and Innovation Center, Cleveland Clinic, Port St. Lucie, FL, USA.
International journal of surgery (London, England)
|June 27, 2024
概括
与瘤学医生相比,大型语言模型 (LLM) 聊天机器人在回答结直肠癌问题方面提供了更高的准确性. 克劳德2.1取得了最高的准确性,在本研究中表现优于医疗专家.
科学领域:
- 人工智能在医学中的应用
- 在瘤学瘤学.
- 自然语言处理自然语言处理.
背景情况:
- 大型语言模型 (LLM) 驱动的聊天机器人越来越多地用于医疗保健.
- 它们在瘤学中的表现,特别是结直肠癌的表现,尚不清楚.
- 这项研究评估了LLM聊天机器人与瘤医生对结直肠癌查询的对比.
研究的目的:
- 为了比较LLM驱动聊天机器人的准确性与瘤医生.
- 评估聊天机器人在解决特定结直肠癌医疗问题的表现.
主要方法:
- 150个结直肠癌问题被提出给八个LLM聊天机器人 (例如,ChatGPT-4,Claude 2.1,Doctor GPT) 和九个瘤医生 (住院医生,研究员,护理人员).
- 答案与指导方针的一致性得分 (1为正确, 0为不正确).
- 聊天机器人和医生的表现基于准确性和分数进行了比较.
主要成果:
- 克劳德2.1获得了最高的准确度 (82.67%),其次是医生GPT (80.45%) 和ChatGPT-4 Turbo (78.44%).
- 一些LLM聊天机器人,包括Claude 2.1和Doctor GPT,与瘤病房住院医生和研究员相比,表现出更好的表现.
- 克劳德2.1在准确性方面也超过了主治医生.
结论:
- 用LLM驱动的聊天机器人可以为结直肠癌查询提供比瘤学医生更准确的医疗信息.
- 这表明LLM有很大的潜力,可以增加瘤学中的医疗信息提供.
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