在新生儿学中偏差风险评估中的ChatGPT-4o:有效性分析
Ilari Kuitunen1,2, Lauri Nyrhi3,4, Daniele De Luca5,6
1Kuopio Pediatric Research Unit, University of Eastern Finland, Kuopio, Finland.
Neonatology
|February 25, 2025
概括
在新生儿研究中,ChatGPT-4o在偏差风险评估中显示出有限的一致性. 需要进行进一步的研究,以提高大语言模型 (LLM) 在偏差评估中的性能.
科学领域:
- 医学研究方法论医学研究方法论.
- 医疗保健中的人工智能
背景情况:
- 有限的研究探索大型语言模型 (LLM) 进行偏差风险评估.
- 不同的结果需要进一步调查LLM的能力.
研究的目的:
- 评估ChatGPT-4o在新生儿研究中偏差风险评估中的表现.
- 为了确定人类和ChatGPT-4o风险偏见判断之间的一致性.
主要方法:
- 分析了2024年的Cochrane新生儿干预审查.
- 使用ChatGPT-4o进行偏差风险评估,并与原始评估进行比较.
- 类间相关系数和科恩的卡帕统计数据被用于对应性评估.
主要成果:
- 分析包括来自9项审查的61项研究,比较了427项判断.
- 总体一致性 (科恩的卡帕) 是0.43,适度一致性 (ICC=0.65).
- 最好的协议是分配隐藏 (κ=0.73);最差的是不完整的结果数据 (κ=-0.03).
结论:
- 聊天GPT-4o在偏差风险评估方面没有达成足够的协议.
- 进一步的研究应该探索其他LLM或为ChatGPT-4o改进的提示技术.
- 目前不建议使用ChatGPT-4o进行偏差风险评估.
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