加快系统审查:一种新的1周选协议,使用基于规则的自动化与人工智能辅助的Python编码
Emely Robleto1,2,3, Lina A Shehadeh1,2,3
1Interdisciplinary Stem Cell Institute, University of Miami Leonard M. Miller School of Medicine, Miami, Florida, United States.
American journal of physiology. Heart and circulatory physiology
|September 12, 2025
概括
传统的系统审查对于不断增长的研究量来说太慢了. 这个新协议使用人工智能辅助的基于规则的自动化来在短短一周内完成系统审查,加速证据合成.
科学领域:
- 生物医学研究和证据综合
- 医疗信息学和研究方法的研究方法.
背景情况:
- 学术出版业的指数增长需要更快的系统审查方法.
- 传统的系统性审查 (6-24个月) 导致临床实施的延迟.
- 现有的自动化工具存在局限性,包括机器学习依赖性和高计算成本.
研究的目的:
- 提出一个新的1周系统审查加速协议.
- 利用基于规则的自动化和人工智能来实现有效的证据综合.
- 克服与传统和当前自动化审查方法相关的障碍.
主要方法:
- 一周的协议使用基于规则的自动化与人工智能协助代码生成.
- 研究人员定义选标准;人工智能语言模型 (Claude,ChatGPT) 作为编码助手.
- 两阶段选:基于规则的标题/摘要选,然后根据规则进行基于规则的全文分析,遵循Cochrane和PRISMA指南.
主要成果:
- 在心力衰竭中的心脏脂肪酸氧化案例研究中证明了应用.
- 通过对电子烟与传统香烟对心肺影响的审查进行验证,处理了3,791条记录.
- 基于规则的系统提供了立即实施,透明度和验证框架,以尽量减少虚假负面.
结论:
- 该协议大大加快了系统审查的速度,使其在1周的时间范围内进行.
- 它消除了机器学习的依赖性,使即时实施和监管合规成为可能.
- 这一进步使得高质量的证据综合在科学学科中更容易获得.
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