Machine learning in drug development: characterizing the effect of 30 drugs on the QT interval using Gaussian process regression, sensitivity analysis, and uncertainty quantification
type: Item
instance of: scholarly article
title: Machine learning in drug development: characterizing the effect of 30 drugs on the QT interval using Gaussian process regression, sensitivity analysis, and uncertainty quantification
zbMATH Open document ID: 1440.62371
author: Francisco Sahli Costabal
author: Kristen Matsuno
author: Jiang Yao
author: Paris Perdikaris
author: Ellen Kuhl
published in: Computer Methods in Applied Mechanics and Engineering
publication date: 2020-04-16T00:00:00Z
Mathematics Subject Classification ID: 62P10
Mathematics Subject Classification ID: 62G08
zbMATH DE Number: 7189789
zbMATH Keywords: machine learning
zbMATH Keywords: Gaussian process regression
zbMATH Keywords: sensitivity analysis
zbMATH Keywords: uncertainty quantification
zbMATH Keywords: finite element analysis
zbMATH Keywords: drug development
describes a project that uses: L-BFGS
describes a project that uses: ABAQUS
Wikidata QID: Q99629392
MaRDI profile type: Publication
full work available at URL: j.cma.2019.01.033
OpenAlex ID: W2912518841
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DOI: 10.1016/J.CMA.2019.01.033
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description: scientific article; zbMATH DE number 7189789