人工智能辅助的统计分析和统计审查:证据 (2023-2025) 和对内科医学的影响
Polish archives of internal medicine
|February 27, 2026
概括
生成型人工智能 (AI) 工具在医疗研究中的统计分析和同行评审方面显示出有前途. 然而,人工智能工具由于性能变化和复杂场景中的局限性而需要人类监督.
科学领域:
- 医学研究方法论医学研究方法论.
- 生物统计学 生物统计学
- 人工智能在医学中的应用
背景情况:
- 统计报告和同行评审对于内部医学研究的可信度至关重要.
- 尽管有建议,但医学期刊的统计质量仍然不理想,正式统计审查率没有改善.
- 生成型人工智能 (AI) 工具在生物医学研究中越来越多地使用,为统计任务提供潜在的支持.
研究的目的:
- 综合关于使用人工智能辅助工具在医学研究中的统计分析和审查方面的证据.
- 评估人工智能的能力和局限性,以支持内部医学研究中的统计任务.
- 讨论人工智能采用对统计实践和同行评审的影响.
主要方法:
- 对2023年至2025年间发表的研究进行叙述性审查.
- 在统计分析和同行评审中对人工智能应用的证据综合.
- 专注于人工智能辅助工具,特别是大型语言模型.
主要成果:
- 人工智能工具可以帮助执行诸如生成分析代码,复制简单统计数据,选择测试和检测形式错误等任务.
- 人工智能性能是可变的,通常是由于不完全考虑统计假设和复杂分析中的可靠性问题而受到限制.
- 当前的人工智能工具不适合完全自主统计分析或同行评审.
结论:
- 在统计分析和审查中有效使用人工智能需要人类统计专业知识,独立验证和上下文判断.
- 人工智能工具应该被视为支持工具,而不是取代人类监督.
- 对内部医学研究的影响是显著的,这种研究以复杂的数据和研究设计为特征.
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