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Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing
In a recent article in Pediatric Nephrology, Olivier Niel and colleagues applied an artificial intelligence algorithm to a clinical problem that continues to challenge experienced pediatric nephrologists: optimizing the target weight of children on dialysis. They compared blood pressure, antihyperte...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6132900/ https://www.ncbi.nlm.nih.gov/pubmed/30003314 http://dx.doi.org/10.1007/s00467-018-4021-4 |
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author | Hayes, Wesley Allinovi, Marco |
author_facet | Hayes, Wesley Allinovi, Marco |
author_sort | Hayes, Wesley |
collection | PubMed |
description | In a recent article in Pediatric Nephrology, Olivier Niel and colleagues applied an artificial intelligence algorithm to a clinical problem that continues to challenge experienced pediatric nephrologists: optimizing the target weight of children on dialysis. They compared blood pressure, antihypertensive medication and intradialytic symptoms in children whose target weight was prescribed firstly by a nephrologist, then subsequently using a machine learning algorithm. Improvements in all outcome measures are reported. Their innovative approach to tackling this important clinical problem appears promising. In this editorial, we discuss the strengths and weaknesses of their study and consider to what extent machine learning strategies are suited to optimizing pediatric dialysis outcomes. |
format | Online Article Text |
id | pubmed-6132900 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-61329002018-09-13 Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing Hayes, Wesley Allinovi, Marco Pediatr Nephrol Editorial Commentary In a recent article in Pediatric Nephrology, Olivier Niel and colleagues applied an artificial intelligence algorithm to a clinical problem that continues to challenge experienced pediatric nephrologists: optimizing the target weight of children on dialysis. They compared blood pressure, antihypertensive medication and intradialytic symptoms in children whose target weight was prescribed firstly by a nephrologist, then subsequently using a machine learning algorithm. Improvements in all outcome measures are reported. Their innovative approach to tackling this important clinical problem appears promising. In this editorial, we discuss the strengths and weaknesses of their study and consider to what extent machine learning strategies are suited to optimizing pediatric dialysis outcomes. Springer Berlin Heidelberg 2018-07-12 2018 /pmc/articles/PMC6132900/ /pubmed/30003314 http://dx.doi.org/10.1007/s00467-018-4021-4 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Editorial Commentary Hayes, Wesley Allinovi, Marco Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing |
title | Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing |
title_full | Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing |
title_fullStr | Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing |
title_full_unstemmed | Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing |
title_short | Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing |
title_sort | beyond playing games: nephrologist vs machine in pediatric dialysis prescribing |
topic | Editorial Commentary |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6132900/ https://www.ncbi.nlm.nih.gov/pubmed/30003314 http://dx.doi.org/10.1007/s00467-018-4021-4 |
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