Machine Learning of Drug Influence Based on iPSC Cardiomyocyte Calcium Transient Signals

M. Juhola, H. Joutsijoki, R. Pölönen, K. Aalto-Setälä
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Abstract

Machine learning was applied to classify potential influence of two drugs on induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) on the basis of peak data detected from calcium transient signals of iPsC-CMs. The study shows that machine learning is capable to analyze such influence.
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基于iPSC心肌细胞钙瞬态信号的药物影响机器学习
基于从诱导多能干细胞- cm的钙瞬态信号中检测到的峰值数据,应用机器学习对两种药物对诱导多能干细胞- cm的潜在影响进行分类。该研究表明,机器学习能够分析这种影响。
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