在样本大小估计中ChatGPT的表现:关于人工智能的初步研究
1University Institute for Primary Care (IuMFE), University of Geneva, 1211 Geneva, Switzerland.
Family practice
|September 5, 2025
概括
像ChatGPT这样的大型语言模型为研究提供了准确的样本大小估计,ChatGPT-4o显示了比ChatGPT-4.0更好的精度. 由于观察到的不一致性,专家验证仍然至关重要.
科学领域:
- 临床研究方法
- 统计计算
- 医疗保健中的人工智能
背景情况:
- 人工智能 (AI) 和大型语言模型 (LLM) 如ChatGPT在临床研究中越来越多地使用.
- 这些人工智能工具对于专业的统计任务,如样本大小估计的实用性尚未得到充分理解.
研究的目的:
- 在进行样本大小估计时评估ChatGPT-4.0和ChatGPT-4o的准确性和可重复性.
- 对比不同版本的ChatGPT在研究中的统计计算的性能.
主要方法:
- 使用ChatGPT-4.0和ChatGPT-4o对24个标准统计场景进行了样本大小计算.
- 准确度是通过对比参考值的绝对百分比误差来衡量.
- 通过比较独立聊天的结果来评估可重复性.
主要成果:
- ChatGPT-4.0和ChatGPT-4o都提供了相当准确的样本大小估计,大多数误差低于5%.
- 与ChatGPT-4.0相比,ChatGPT-4o显示出更高的准确性和稍微更好的可重复性.
- 观察到的不一致性表明需要仔细审查人工智能产生的估计.
结论:
- 在标准研究场景中,ChatGPT-4.0和ChatGPT-4o可以作为初步样本大小估计的有用工具.
- 用户必须谨慎,并寻求专家验证人工智能生成的统计结果.
- 复杂的统计任务和更广泛的AI模型需要进一步调查.
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