轻度认知障碍初级查的文本对话分析:发展和验证研究
Changyu Wang1,2, Siru Liu3, Aiqing Li4
1Department of Medical Informatics, West China Medical School, Sichuan University, Chengdu, China.
Journal of medical Internet research
|December 29, 2023
概括
在轻度认知障碍 (MCI) 查方面,ChatGPT显示出有前景. 标准化提示提高了它的准确性,但它不能取代对认知障碍的临床诊断.
科学领域:
- 神经学 神经学
- 人工智能的人工智能
- 计算语言学 计算语言学
背景情况:
- 专门的AI模型在诊断认知障碍方面取得了成功.
- 像ChatGPT这样的大型语言模型 (LLM) 仅仅使用文本来完成此任务的有效性尚未得到充分证实.
研究的目的:
- 评估ChatGPT在轻度认知障碍 (MCI) 的初级查中的表现.
- 在认知查中标准化快速设计元素,以获得最佳的LLM性能.
主要方法:
- 利用了174名参与者的文字对话 (70%的培训,30%的测试).
- 开发了一个包含词汇,语法和语义的5部分提示.
- 包括MCI严重性的指标:舌尖现象,复杂的想法困难和记忆问题.
主要成果:
- 在训练套件上,GPT-4模型取得了高性能 (灵敏度:0.86,特异性:0.95,AUC:0.91).
- 在测试组中,性能仍然很强 (灵敏度:0.77,特异性:0.83,AUC:0.80).
- 关键指标显著区分了MCI和认知正常的参与者 (P<.001).
结论:
- 聊天GPT证明了对潜在的MCI的初级查的有效性.
- 标准化提示,特别是临床医生的提示,可以进一步提高模型性能.
- 聊天GPT作为一个查工具,并不是专业临床诊断的替代品.
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