聊天GPT-4在护理研究:在随机对照试验中对偏差风险的方法评估
Metin Tuncer1, Gülsüm Zekiye Tuncer2
1Department of Nursing Fundamentals, Gümüşhane University, Gümüşhane, Turkey.
概括
人工智能 (AI) 在系统审查中显示出偏差评估的潜力,但像ChatGPT-4o这样的当前工具需要显著改进才能可靠地使用. 人类监督对于人工智能辅助的偏见风险评估至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 系统审查方法论 系统审查方法论
背景情况:
- 在系统性审查中对偏见的评估是主观的,耗时的.
- 人工智能 (AI) 在偏见评估中提供了提高效率和一致性的潜力.
- 人工智能对偏见评估的有效性需要进一步调查.
研究的目的:
- 评估ChatGPT-4o在偏差评估中的有效性,使用修订后的Cochrane风险偏差2 (RoB2) 工具.
- 将评估重点放在护理研究中的随机对照试验 (RCT) 上.
主要方法:
- 聊天GPT-4o提供了RoB2评估指南 (PDF).
- 人工智能对80个开放式RCT进行了偏见评估.
- 结果与使用科恩加权卡帕分析的元分析作者评估进行了比较.
主要成果:
- 在RoB2域中,ChatGPT-4o和作者之间的协议通常很低.
- 科恩的kappa表明缺乏结果数据 (D3) 和报告结果的选择 (D5) 的协议不佳.
- 准确性各不相同,在D5 (0.81) 最高,在D1 (0.60) 最低;F1得分和特异性/敏感性显示混合结果.
结论:
- 聊天GPT-4o需要大幅度改进,才能成为一个可靠的偏见风险评估工具.
- 人工智能工具可以加快偏见评估,但当前版本需要谨慎的集成和人类监督.
- 在基于证据的评估中,人工智能辅助的偏见评估需要在影响临床决策之前仔细验证.
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