聊天GPT,双子座,副驾驶员和克劳德的准确性与膜整形相关的问题
Seher Köksaldı1, Mustafa Kayabaşı2, Ceren Durmaz Engin3
1Department of Ophthalmology, Agri Ibrahim Cecen University, 04200, Agri, Turkey. seherkoksaldi@gmail.com.
Aesthetic plastic surgery
|July 21, 2025
概括
在四个大型语言模型 (LLM) 中,ChatGPT在上眼白造形问题上的准确性和相关性表现最好. 它的详细反应为眼科医生提供了宝贵的临床指导.
科学领域:
- 眼科医生 眼科 眼科
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 评估了四个大型语言模型 (LLM),以评估它们在回答关于上眼白造形术的问题上的表现.
- 评估的重点是医学准确性,临床相关性,反应长度和可读性.
研究的目的:
- 为了比较ChatGPT,Gemini,Copilot和Claude在提供关于上眼白造形术的信息方面的有效性.
- 评估LLM产生的临床应用反应的质量和复杂性.
主要方法:
- 对每个法学士提出了关于上眼白造形的标准问题.
- 眼科医生通过使用利克特尺度来评估答案的准确性和相关性.
- 使用已确定的指标分析了响应长度和可读性.
主要成果:
- 聊天GPT获得了最高的"高度准确" (80%) 和临床相关 (86.7%) 响应率.
- 副驾驶生成了最短的响应,而ChatGPT生成了最长的响应.
- 所有的LLM答案都需要先进的阅读技能,Copilot是最复杂的.
结论:
- 聊天GPT证明了对上眼白造形信息的卓越医疗准确性和临床相关性.
- 虽然LLM的反应很复杂,但可以为眼科医生提供宝贵的指导.
- 进一步的研究可能会探索优化医学专业人员的LLM输出.
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