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在神经外科研究文章的同行评审中利用人工智能
Ali A Mohamed1,2, Daniel Colome3, Jack Yang3
1Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, USA. amohamed2020@health.fau.edu.
Neurosurgical review
|September 3, 2025
概括
人工智能 (AI) 在预测神经外科手稿接受度方面表现出适度的准确性. 未来的人工智能模型可能通过改善期刊协作和同意的预测准确性来简化同行审查.
科学领域:
- 神经外科
- 人工智能
- 科学出版
背景情况:
- 传统的同行评审是耗时的,延迟了研究的传播.
- 人工智能 (AI) 为优化手稿审查提供了一个潜在的解决方案.
- 分析神经外科预印,以评估人工智能对出版结果的预测能力.
研究的目的:
- 评估当前人工智能模型 (ChatGPT 4o,Gemini,Copilot) 在预测神经外科手稿的接受或拒绝方面的有效性.
- 在接受和假定不接受的预印件之间比较期刊指标.
- 在预测同行评审结果时确定AI的准确性.
主要方法:
- 来自预印服务器的51个神经外科预印件 (头骨底部和脊柱) 的分析.
- 已发布的预版与存储在服务器上超过12个月的预版的比较.
- 人工智能模型根据出版前的文献预测接受/拒绝.
主要成果:
- 人工智能模型的性能显著低,准确度在40%至66.67%之间.
- 在预测被接受或不被接受的预印之间,没有发现期刊指标 (影响因子,引用分数) 的显著差异.
- 不管人工智能预测如何, 接受的预印显示出更高的期刊指标.
结论:
- 目前的人工智能模型在预测神经外科手稿同行评审结果的准确性有限.
- 未来的人工智能开发,与期刊合作和作者同意,可以提高预测准确性.
- 如果准确性和数据访问性得到改善,人工智能有可能简化同行评审过程.
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