Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods

• Main Authors: Kandasamy, K, Chuah, J.K.C, Su, R, Huang, P, Eng, K.G, Xiong, S, Li, Y, Chia, C.S, Loo, L.-H, Zink, D
• Other Authors: OBSTETRICS & GYNAECOLOGY
• Format: Article
• Published: 2020
• Subjects: acute kidney failure; automated pattern recognition; bioassay; cell culture; cell differentiation; cell survival; drug effects; human; induced pluripotent stem cell; kidney proximal tubule; machine learning; pathology; preclinical study; procedures; reproducibility; sensitivity and specificity; toxicity testing; Acute Kidney Injury; Biological Assay; Cell Differentiation; Cell Survival; Cells, Cultured; Drug Evaluation, Preclinical; Humans; Induced Pluripotent Stem Cells; Kidney Tubules, Proximal; Machine Learning; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Toxicity Tests
• Online Access: https://scholarbank.nus.edu.sg/handle/10635/180325
• Institution: National University of Singapore

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