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Complex versus simple models: ion-channel cardiac toxicity prediction

There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established large-scale biophysic...

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Autor principal: Mistry, Hitesh B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5804316/
https://www.ncbi.nlm.nih.gov/pubmed/29423349
http://dx.doi.org/10.7717/peerj.4352
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author Mistry, Hitesh B.
author_facet Mistry, Hitesh B.
author_sort Mistry, Hitesh B.
collection PubMed
description There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established large-scale biophysical cardiac models and a simple linear model B(net) was conducted. Three ion-channel data-sets were extracted from literature. Each compound was designated a cardiac risk category using two different classification schemes based on information within CredibleMeds. The predictive performance of each model within each data-set for each classification scheme was assessed via a leave-one-out cross validation. Overall the B(net) model performed equally as well as the leading cardiac models in two of the data-sets and outperformed both cardiac models on the latest. These results highlight the importance of benchmarking complex versus simple models but also encourage the development of simple models.
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spelling pubmed-58043162018-02-08 Complex versus simple models: ion-channel cardiac toxicity prediction Mistry, Hitesh B. PeerJ Mathematical Biology There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established large-scale biophysical cardiac models and a simple linear model B(net) was conducted. Three ion-channel data-sets were extracted from literature. Each compound was designated a cardiac risk category using two different classification schemes based on information within CredibleMeds. The predictive performance of each model within each data-set for each classification scheme was assessed via a leave-one-out cross validation. Overall the B(net) model performed equally as well as the leading cardiac models in two of the data-sets and outperformed both cardiac models on the latest. These results highlight the importance of benchmarking complex versus simple models but also encourage the development of simple models. PeerJ Inc. 2018-02-05 /pmc/articles/PMC5804316/ /pubmed/29423349 http://dx.doi.org/10.7717/peerj.4352 Text en ©2018 Mistry http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Mathematical Biology
Mistry, Hitesh B.
Complex versus simple models: ion-channel cardiac toxicity prediction
title Complex versus simple models: ion-channel cardiac toxicity prediction
title_full Complex versus simple models: ion-channel cardiac toxicity prediction
title_fullStr Complex versus simple models: ion-channel cardiac toxicity prediction
title_full_unstemmed Complex versus simple models: ion-channel cardiac toxicity prediction
title_short Complex versus simple models: ion-channel cardiac toxicity prediction
title_sort complex versus simple models: ion-channel cardiac toxicity prediction
topic Mathematical Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5804316/
https://www.ncbi.nlm.nih.gov/pubmed/29423349
http://dx.doi.org/10.7717/peerj.4352
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