评估ChatGPT在眼科中的表现:对其成功和缺陷的分析
Fares Antaki1,2,3,4, Samir Touma1,2,3, Daniel Milad1,2,3
1Department of Ophthalmology, Université de Montréal, Montréal, Quebec, Canada.
Ophthalmology science
|June 19, 2023
概括
在眼科问题上,ChatGPT显示出有希望的准确性,ChatGPT Plus显示出与传统模型相比的改进. 人工智能模型的进一步专业化可能会提高特定医疗领域的性能.
科学领域:
- 人工智能的人工智能
- 眼科医生 眼科 眼科
- 医学教育 医学教育
背景情况:
- 基金会模型是先进的AI系统,在庞大的数据集上进行预训练.
- 像ChatGPT这样的大型语言模型 (LLM) 在专业应用中越来越多地被评估.
- 在医学问答中评估AI准确度对于教育和临床整合至关重要.
研究的目的:
- 评估一个大型语言模型ChatGPT在回答眼科相关问题的准确性.
- 为了比较两个ChatGPT版本 (Legacy和Plus) 在眼科知识评估上的表现.
主要方法:
- 使用已建立的问题库 (BCSC和OphthoQuestions) 创建了两个模拟眼科考试.
- 聊天GPT (旧版本和Plus版本) 每个回答了260个多选择题.
- 后勤回归分析了影响准确性的因素,包括考试部分和问题难度.
主要成果:
- 与传统模式 (55.8%和42.7%) 相比,ChatGPT Plus实现了更高的准确性 (59.4%在BCSC上,49.2%在OphthoQuestions上).
- 准确性与询问方便性有积极的相关性.
- 传统模型显示了各个子专业的性能差异,而ChatGPT Plus显示了更一致的结果.
结论:
- 在模拟眼科检查中,ChatGPT表现出令人鼓舞的准确性.
- 特定领域的预培训可能是必要的,以优化专业眼科领域的LLM绩效.
- 人工智能工具显示了眼科教育和知识评估的潜力.
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