公共与学术关于ChatGPT在医疗保健中的讨论:混合方法研究研究
Patrick Baxter1, Meng-Hao Li1, Jiaxin Wei1
1Schar School of Policy and Government, George Mason University, 3351 Fairfax Dr, Arlington, VA, 22201, United States, 1 (703) 993-8999.
JMIR infodemiology
|June 23, 2025
概括
关于医疗保健中的人工智能 (AI) 大语言模型 (LLM),公众的情绪在很大程度上是积极的,但对心理健康应用存在担忧. 这项研究比较了公众和专家对公共卫生中的LLM的看法.
科学领域:
- 公共卫生 公共卫生
- 人工智能的人工智能
- 计算语言学 计算语言学
背景情况:
- 人工智能大语言模型 (LLM) 的出现引发了关于它们的好处和伦理影响的辩论.
- 现有的研究缺乏对公共卫生中的LLM的公众认知与专家意见的清晰理解.
研究的目的:
- 探索公众和学术专家对LLM的观点的差异,特别是OpenAI的ChatGPT.
- 了解LLM在医疗保健环境中的未来作用.
主要方法:
- 使用R和GPT-3.5的混合情绪分析方法实现了84%的准确性.
- 结构性主题建模确定了LLMs的8个关键讨论主题.
主要成果:
- 对于LLM在患者护理和临床决策中的整合,主要是积极的情绪.
- 关于LLM适用于心理健康支持和患者沟通的相关问题.
结论:
- 在公共卫生方面,LLM具有变革性的潜力,但道德和实际挑战需要注意.
- 将公众话语与学术观点进行比较,为关于在医疗保健中采用LLM的辩论提供了信息.
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