聊天GPT使药物易于吞:一个探索性病例研究简化放射学报告
Katharina Jeblick1,2,3, Balthasar Schachtner4,5, Jakob Dexl4,5
1Department of Radiology, LMU University Hospital, LMU Munich, Munich, Germany. katharina.jeblick@med.uni-muenchen.de.
European radiology
|October 4, 2023
概括
患者正在使用ChatGPT来简化医疗报告,但质量各不相同. 虽然一般准确,但简化报告可能含有错误,需要专家监督,以确保在放射学中安全的患者通信.
科学领域:
- 人工智能在医学中的应用
- 医疗信息学 医疗信息学
- 放射学报告 放射学报告
背景情况:
- 患者越来越多地使用像ChatGPT这样的大型语言模型 (LLM) 来获取医疗信息.
- 用LLM生成的简化放射学报告对患者理解的质量和安全性在很大程度上是未知的.
- 这会影响患者与医生的互动和临床工作流程.
研究的目的:
- 通过ChatGPT简化评估放射学报告的质量.
- 确定在医学中使用基于LLM的文本简化方面的挑战和机会.
- 在患者沟通中安全整合人工智能工具的信息.
主要方法:
- 虚构的放射学报告被简化使用ChatGPT与一个特定的提示.
- 一个调查问卷评估了15名放射科医生对事实正确性,完整性和潜在危害的评级.
- 使用了利克特比例分析和诱导式自由文本分类.
主要成果:
- 大多数放射科医生发现简化的报告事实上是正确的,完整的,没有危害.
- 然而,特定的不准确情况,遗漏和潜在的有害内容被确定.
- 放射科医生指出需要专家医疗监督.
结论:
- 像ChatGPT这样的LLM显示出在放射学中加强以患者为中心的护理的巨大潜力.
- 适应和专家监督对于最小化风险和最大化收益至关重要.
- 需要进一步的研究来完善医学文本简化的LLM应用.
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