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Updated: May 13, 2025

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在药物发现和开发中解决不平衡的分类问题,使用随机森林,支持矢量机,AutoGluon-Tabular和H2OAutoML

Ayush Garg1, Narayanan Ramamurthi2, Shyam Sundar Das3

  • 1TCS Research (Life Sciences Division), Tata Consultancy Services Limited, Noida 201303, India.

Journal of chemical information and modeling
|April 15, 2025
PubMed
概括

本研究分析了不平衡分类的数据平衡技术,发现结合外部方法比内部方法更能提高性能. 建议探索多种技术,以获得机器学习和AutoML的最佳结果.

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Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
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Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
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