机器学习在实验动物设施管理中的应用进展与展望  

A review and promising future directions of machine learning in laboratory animal facility management

作　　者：徐骁 陈琦[1] XU Xiao;CHEN Qi(Laboratory Animal Center,Huazhong University of Science and Technology,Wuhan 430030,China)

机构地区：[1]华中科技大学实验动物中心,武汉430030

出　　处：《中国比较医学杂志》2024年第1期103-113,共11页Chinese Journal of Comparative Medicine

摘　　要：随着我国实验动物设施智能化水平逐步提升,积累了大量能够反映设施运行真实状态的数据。由于分析手段的缺乏,数据价值未得到充分的挖掘。在大数据背景下,机器学习(machine learning)已经在生物医疗、建筑科学等领域取得了显著的成果,也为其在实验动物设施管理中的应用提供了参考。本文对国内外机器学习应用于实验动物设施各系统中的内容、方法和模式进行了综述与展望。As the intelligence level gradually improves in domestic laboratory animal facilities,a large amount of valuable data have been accumulated.These data have not been fully exploited because of the lack of analytical method.In the context of big data,machine learning has achieved remarkable result in biomedicine,building science,and other fields,and provides a reference for its application in laboratory animal facility management.In this article,the contents,methods and models of machine learning applied to various systems of laboratory animal facilities at home and abroad are reviewed and discussed.

关 键 词：机器学习 实验动物设施 屏障设施 

分 类 号：R-33[医药卫生]