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English(EN) Scaffold splits hide structural-frontier failures in ADMET models

新的评估方法揭示了分子性质模型中隐藏的失败

研究人员发现,常用的分子性质模型评估方法存在重大缺陷,特别是用于 ADMET(吸收、分布、代谢、排泄和毒性)预测的模型。一种新的“结构前沿”拆分方法,保留了化学上最偏远的支架组,揭示了标准的基于支架的拆分可能会隐藏重大的性能下降。与标准对照相比,这种前沿拆分将主要误差中值提高了 87.0%,表明当前的评估实践可能高估了模型对新化学结构的可靠性。 AI

影响 强调了化学信息学中需要更鲁棒的评估指标,以确保对新分子结构的可靠预测。

排序理由 该项目是一篇研究论文,详细介绍了特定领域中机器学习模型的新评估方法。 [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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新的评估方法揭示了分子性质模型中隐藏的失败

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该项目是一篇研究论文,详细介绍了特定领域中机器学习模型的新评估方法。 [lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Jiacheng Zheng, Chang Guo, Zixuan Wang, Xinyu Liu ·

    支架拆分隐藏ADMET模型中的结构前沿失败

    arXiv:2607.10729v1 Announce Type: new Abstract: Molecular property models are commonly evaluated by holding out Bemis--Murcko scaffolds, yet a scaffold identifier is only one notion of chemical unfamiliarity. We introduce a label-free structural-frontier split that reserves the s…