机器学习在实验动物设施管理中的应用进展与展望
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华中科技大学实验动物中心


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

1.LaboratoryAnimalCenter,HuazhongUniversityofScienceandTechnology;2.Laborotary animal center,Huazhong University of science and technology

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    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,数据价值没有得到充分的挖掘。在大数据背景下,机器学习 (Machine Learning)算法已经在生物医疗、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方法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。

    Abstract:

    As the intelligence level gradual improving in domestic laboratory animal facilities,a large amount of valuable data has been accumulated. The data has not been fully exploited due to lacking of analytical means. In the context of Big data, Machine learning algorithms have achieved remarkable results in biomedical, building science and other fields, and also provide a reference for their application in laboratory animal facility management. In this paper, the contents, methods and models of machine learning methods applied to various systems of laboratory animal facilities at home and abroad are reviewed and prospected.

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历史
  • 收稿日期:2023-08-01
  • 最后修改日期:2023-08-08
  • 录用日期:2024-01-05
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