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Updated: Jan 28, 2026

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使用hiPSC-CM MEA数据进行心脏安全评估的堆叠集团机器学习.

Muhammad Adnan Pramudito1, Yunendah Nur Fuadah2, Yoo Seok Kim3

  • 1Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, 39177, Republic of Korea.

Annals of biomedical engineering
|January 26, 2026
PubMed
概括

一个新的堆叠组合模型使用hiPSC-CM试验的简单电生理学数据准确预测Torsades de Pointes (TdP) 风险,改进了药物安全性测试的单模型方法.

关键词:
心脏安全药理学心脏安全药理学现场潜在持续时间 (FPD)机器学习是机器学习.多个电极阵列 (MEA)堆叠组合机器学习机器学习在Torsades de Pointes (TdP) 的位置上由hiPSC衍生的心肌细胞.

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