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Updated: Jun 4, 2025

Early Detection of Drug-Induced Renal Hemodynamic Dysfunction Using Sonographic Technology in Rats
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Early Detection of Drug-Induced Renal Hemodynamic Dysfunction Using Sonographic Technology in Rats

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机器学习辅助分类RASAR建模用于精选的一组口服活性药物的毒性潜力

Arkaprava Banerjee1, Kunal Roy2

  • 1Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.

Scientific reports
|January 4, 2025
PubMed
概括

这项研究开发了机器学习 (ML) 模型,使用分类阅读跨结构-活动关系 (c-RASAR) 方法来预测药物毒性. 最好的c-RASAR模型准确地识别了药物的潜在脏毒性,有助于更安全的药物开发.

关键词:
阿尔卡阿尔卡 (Arka Arka) 是一个城市.机器学习 机器学习毒性 毒性 毒性在QSAR中使用QSAR.排名差异 (SRD) 的总和在c-RASAR中使用.这就是T-SNENE.

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