聊天机器人文学搜索在辐射瘤学中的实用性
Justina Wong1, Conley Kriegler2, Ananya Shrivastava1
1Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada.
概括
像ChatGPT这样的人工智能工具在瘤学文献评论中显示出潜力,但产生了许多不存在的论文. 对人工智能产生的内容的验证对于在放射瘤学中可靠的临床使用至关重要.
科学领域:
- 在瘤学瘤学.
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 和自然语言处理 (NLP) 工具在瘤学中提供了潜在的好处,包括帮助医学文献检索和患者支持.
- 然而,人工智能能够产生可信但不准确的信息,这对临床应用提出了重大挑战.
研究的目的:
- 本研究评估了使用ChatGPT (3.5版本) 进行放射瘤学临床文献审查的有效性,益处和局限性.
- 该研究特别评估了其在识别各种瘤部位的放射治疗治疗选择中的有用性.
主要方法:
- 采用横截面研究设计,利用ChatGPT 3.5生成关于放射治疗七种瘤类型的文献搜索.
- 每个瘤部位发出了五次提示,每种类型的目标是多达50份出版物. 出版物与Scopus数据库进行了验证,并被分类为正确,无关或不存在.
主要成果:
- 在350个生成的出版物中,44个是正确的,298个不存在,8个不相关.
- 所有生成论文的平均出版年为2011年 (2009年为正确论文),平均影响因子为38.8 (113.8为正确论文).
- 在正确和不存在的论文中,在瘤部位之间观察到出版年,影响因子和引用数量的显著变化.
结论:
- 聊天GPT 3.5 展示了辐射瘤学文献评论的潜在实用性和重大局限性.
- 调查结果强调,严格验证人工智能产生的输出,制定质量保证协议和对人工智能偏差进行持续研究对于安全的临床整合至关重要.
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