人工智能用于证据综合的科学:人工智能为自动文献选提供了多么好的工具?
Minghao Ruan1, Junhao Fan2, Mingkai Liu3
1The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, the Naval Medical University, Shanghai, China.
BMC medical research methodology
|August 26, 2025
概括
人工智能工具对文献选具有前景,但尚未成为独立的解决方案. 将人工智能与人类专业知识相结合的混合方法可以提高证据综合的效率和准确性.
科学领域:
- 医疗信息学
- 研究中的人工智能
背景情况:
- 文献选对于综合证据至关重要,但耗时且资源密集.
- 人工智能 (AI) 提供了自动化文献选的潜力,但其准确性和有效性需要评估.
研究的目的:
- 在文献选中评估五种人工智能工具 (ChatGPT 4.0,Claude 3.5,Gemini 1.5,DeepSeek-V3和RobotSearch) 的性能.
- 为了比较诊断准确度指标,包括错误负数 (FNF) 和错误正数 (FPF),以及查时间.
主要方法:
- 一项使用1000个出版物的诊断准确性研究.
- 该队列包括500个随机对照试验 (RCT) 和500个其他出版物.
- 评估了五种人工智能工具在识别相关文献方面的表现.
主要成果:
- 在RCT中,RobotSearch的FNF值最低 (6.4%),而Gemini的FNF值最高 (13.0%).
- 对于其他出版物来说,大型语言模型 (LLM) 与机器人搜索 (22.2%) 相比具有显著较低的FPF.
- 每篇文章的选时间各不相同,Gemini (1.2s) 和ChatGPT (1.3s) 是最快的.
结论:
- 人工智能工具在文献选方面具有显著的潜力,但尚未适合独立使用.
- 这些人工智能工具可以作为证据综合过程中的有价值的辅助工具.
- 建议采用混合方法,将人类专业知识与人工智能结合起来,以优化文献选的效率和准确性.
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