探索人工智能,大型语言模型的作用:将以患者为中心的信息和临床决策支持能力与妇科瘤学指南进行比较
Lee Reicher1,2,3,4, Guy Lutsker3,4, Nadav Michaan1,2
1Department of Gynecologic Oncology, Lis Hospital for Women, Tel Aviv Medical Center, Tel Aviv, Israel.
大型语言模型 (LLM) 在回答妇科癌症问题方面表现有前途,为患者和提供者提供清晰的信息. 虽然它们对于常见的查询是准确的,但它们在复杂的案例和区域指导方针变化方面遇到了困难.
科学领域:
- 在瘤学瘤学.
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 个性化护理对于改善妇科癌症的结果至关重要.
- 大型语言模型 (LLM) 为可访问的医疗信息提供了潜力.
- 评估医疗保健中的AI工具对于了解它们的实用性至关重要.
研究的目的:
- 评估两个LLM,ChatGPT和谷歌的Bard在回答妇科癌症管理问题的表现.
- 根据既定的临床指南评估LLM反应的准确性和适当性.
- 确定LLMs作为妇科瘤学信息工具的潜在作用.
主要方法:
- 开发了一组关于妇科瘤学的患者和临床医生的观点问题.
- 来自ChatGPT和Bard的响应被生成和记录.
- 评估了LLM答案是否符合国家综合癌症网络和欧洲妇科瘤学会的指导方针.
主要成果:
- 对于常见的宫癌查和与BRCA相关的问题,LLM在很大程度上提供了适当的答案.
- 对复杂和有争议的妇科瘤病例的反应不那么有用.
- 临床医学师表现出对区域指导方针的变化缺乏认识,但为患者提供了实用建议.
结论:
- 临床医生可以为患者和医疗保健提供者提供有关妇科癌症的有价值,可理解的信息.
- 需要进一步发展以解决临床指南的复杂性和区域差异.
- 临床医疗法可以作为补充工具,以增强患者和护理人员的理解和管理支持.
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