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Updated: Jul 19, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

评估人工智能对系统审查的文章选效率

Yu-Ting Chan¹, Jilaine Elliscent Abad¹, Serge Dibart¹

¹Department of Periodontology, Henry M. Goldman School of Dental Medicine, Boston University, 635 Albany Street, Boston, MA 02118, United States.

Journal of dentistry

|July 27, 2024

概括

像ASReview这样的人工智能 (AI) 工具通过对文章进行优先排序来显著提高系统审查效率. 这个人工智能程序可以节省大约60%的时间和精力,通常需要文章选.

科学领域:

医疗信息学医学信息学
医疗保健中的人工智能
系统审查方法论系统审查方法论

背景情况:

机器学习 (ML) 和人工智能工具提高了医学和学术界的效率.
ASReview 是一个人工智能程序,旨在通过自动化文章优先级来简化系统性审查.
本研究评估了ASReview的查效率和影响因素.

研究的目的:

在系统性审查中检查ASReview的选效率.
确定影响ASReview效率的因素.

主要方法:

在PubMed和科学网上搜索了六个牙周学主题.
训练有素的ASReview与ML优化相关/不相关的文章.
根据标准化的未经审查的文章和时间支出评估选效率.

主要成果:

平均有60.2%的文章不需要进行广泛的选.
所有相关的文章都被确定在前39.8%的审查出版物中.
不同的培训方法或文章比率没有发现显著的效率差异.

结论:

由于ML功能,ASReview在选效率上平均提高了60.2%.
人类的辨别能力对于有效训练像ASReview这样的AI工具至关重要.
ASReview有可能在文章选中节省大约60%的时间和精力.

关键词:

在ASReview中,我们会对此进行评估.人工智能的人工智能是人工智能.效率效率是指效率是指效率.系统性审查系统性审查

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