热门大型语言模型在青光眼患者教育中的表现:一项随机对照研究
Yuyu Cao1,2,3,4, Wei Lu5, Runhan Shi1,2,3,4
1Department of Ophthalmology, Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China.
Advances in ophthalmology practice and research
|March 31, 2025
概括
这项研究比较了四个大型语言模型 (LLM) 对于玻璃眼患者教育. 白川2和ChatGPT-4.0在提供患者友好和信息化的反应方面表现出相似的有效性.
科学领域:
- 人工智能在医学中的应用
- 眼科医生 眼科 眼科
- 医疗信息学 医疗信息学
背景情况:
- 大型语言模型 (LLM) 正在改变知识获取,但它们在治疗眼等疾病的患者教育中的应用尚未得到充分探索.
- 有效的患者教育对于管理慢性眼睛疾病,如玻璃眼瘤至关重要.
研究的目的:
- 为了比较四种常见的LLM (Qwen,Baichuan 2,ChatGPT-4.0,PaLM 2) 对于青光眼患者教育的性能.
- 评估LLM对于向患者提供与眼有关的信息的适用性.
主要方法:
- 高级眼科医生进行初步评估,对常见的玻璃眼病问题的LLM答案进行评分.
- 使用中国可读性平台进行可读性评估.
- 现实世界的临床测试与29名青光眼患者和眼科医生参与,评估聊天机器人的答案的正确性,完整性,可读性,帮助性和安全性.
主要成果:
- 白川2和ChatGPT-4.0最初的表现优于Qwen和PaLM 2.
- 聊天GPT-4.0表现出较高的推阅读年龄和难度得分.
- 在临床测试中,Baichuan 2和ChatGPT-4.0显示了类似的高性能,患者和眼科医生得分之间没有显著差异.
结论:
- 白川2和ChatGPT-4.0被确定为绿眼病患者教育的领先LLM.
- 这些模型提供了有希望的,可行的工具,以提高患者对绿眼治疗的理解和参与.
关键词:
在白川,白川就是白川.聊天GPT 聊天GPT 的意思聊天机器人 聊天机器人眼光障碍 眼光障碍 眼光障碍 眼光障碍大型语言模型.在 PaLMLM 里面.患者教育 患者教育这就是Qwen Qwen.更多相关视频
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