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

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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
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Institution:	National University of Singapore

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spelling	sg-nus-scholar.10635-1803252024-04-15T02:39:48Z Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods 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 OBSTETRICS & GYNAECOLOGY PHARMACOLOGY 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 Scientific Reports 5 12337 2020-10-26T08:29:16Z 2020-10-26T08:29:16Z 2015 Article 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 (2015). Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods. Scientific Reports 5 : 12337. ScholarBank@NUS Repository. 20452322 https://scholarbank.nus.edu.sg/handle/10635/180325 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ Unpaywall 20201031
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	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
spellingShingle	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 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 Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods
description	Scientific Reports
author2	OBSTETRICS & GYNAECOLOGY
author_facet	OBSTETRICS & GYNAECOLOGY 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
format	Article
author	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
author_sort	Kandasamy, K
title	Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods
title_short	Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods
title_full	Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods
title_fullStr	Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods
title_full_unstemmed	Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods
title_sort	prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods
publishDate	2020
url	https://scholarbank.nus.edu.sg/handle/10635/180325
_version_	1800914586712408064

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

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