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Updated: Jun 16, 2025

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民主化化学信息学:使用自动化KNIME工作流程进行可解释的化学分组

José T Moreira-Filho1, Dhruv Ranganath2, Mike Conway3

  • 1National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA. teofilo.moreirafilho@nih.gov.

Journal of cheminformatics
|August 16, 2024
PubMed
概括

本研究介绍了KNIME中一个用户友好的化学分组工作流程,简化了数据分析而不需要编码. 它集成了先进的机器学习和解释工具,用于可访问的化学分类和理解.

关键词:
化学品的分组是化学品的分组.数据可视化数据可视化可解释的人工智能功能选择 功能选择在KNIME工作流程中.机器学习是机器学习.谢普利添加剂的解释监督的分类是监督的分类.没有监督的集群.

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