评估ChatGPT作为基于人工智能的大型语言模型的实用性,以获得有关近视问题的答案
Sayantan Biswas1, Nicola S Logan1, Leon N Davies1
1School of Optometry, College of Health and Life Sciences, Aston University, Birmingham, UK.
概括
聊天GPT通常提供良好的近视信息质量,但发现一些不准确. 需要进一步评估以了解其在医疗保健应用中的局限性.
科学领域:
- 眼科医生 眼科 眼科
- 人工智能的人工智能
- 医疗信息系统 医疗信息系统
背景情况:
- 像ChatGPT这样的人工智能语言模型越来越多地用于医疗保健.
- 这些模型可以模拟人类对话,并在各种领域提供信息.
- 它们在医学教育,研究和临床实践中的应用正在扩大.
研究的目的:
- 评估ChatGPT提供关于近视问题的信息的准确性和质量.
- 评估ChatGPT在回答与近视相关的各种问题的表现.
主要方法:
- 他们提出了11个问题,涵盖了近视的9个类别 (例如,原因,治疗,预后).
- 每个问题都在单独的会话中五次输入ChatGPT.
- 一个由五名 optometry 专家组成的小组使用利克特尺度对答案的准确性和质量进行了评分.
主要成果:
- 在11个近视相关问题中,ChatGPT为10个提供了高质量的信息 (中位数为4.0).
- 一个问题得到了可接受的答案 (中位数为3.0).
- 在总共275个答案中,73%被评为好或非常好,5.4%被评为差或非常差.
结论:
- 聊天GPT展示了快速传播有关近视的信息的潜力.
- 该研究强调,由于存在不准确性,需要对人工智能生成的医疗信息进行批判性评估.
- 意识到ChatGPT的局限性至关重要,以防止在临床和教育环境中出现潜在的误解.
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