大型语言模型对医生患者沟通的潜在影响:前列腺癌的案例研究
Marius Geantă1,2,3, Daniel Bădescu1,4, Narcis Chirca1,4
1Department of Urology, "Carol Davila" University of Medicine and Pharmacy, 8 Eroii Sanitari Blvd., 050474 Bucharest, Romania.
大型语言模型 (LLM) 在改善前列腺癌护理的医生与患者沟通方面表现有前途. 与患者指南相比,ChatGPT表现出更高的准确性和用户友好性,这表明了改善医疗保健信息传递的潜力.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 数字健康传播数字健康传播
背景情况:
- 大型语言模型 (LLM) 越来越多地融入医疗保健.
- 法律学士课程为医生与患者之间的沟通增强提供了潜力,特别是在治疗前列腺癌等疾病时.
研究的目的:
- 评估罗马尼亚著名的LLM (ChatGPT,Gemini,Co-Pilot) 在前列腺癌患者信息方面的有效性.
- 将LLM的成绩与罗马尼亚官方患者指南进行比较.
- 评估LLM在个性化和可访问的患者沟通方面的潜力.
主要方法:
- 涉及三个LLM (ChatGPT 3.5,Gemini Pro,Co-Pilot) 和罗马尼亚患者指南的比较研究.
- 由八名医疗专业人员进行随机和盲目的评估.
- 评估标准包括准确性,及时性,全面性和用户友好性.
主要成果:
- 在准确性和用户友好性方面,LLM,特别是ChatGPT,总体上表现优于患者指南.
- 该研究探讨了LLM在罗马尼亚语中提供可比或优异信息的能力.
- 观察到LLM的潜力是个性化沟通和改善信息可访问性.
结论:
- 通过提供准确和可访问的信息,LLM显示了提高医疗保健沟通的巨大潜力.
- 在LLM绩效的变化需要量身定制的实施策略.
- 在临床环境中优化LLM的使用需要对其能力和局限性的细微了解.
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