Cargando…

Unintended consequences of machine learning in medicine?

Machine learning (ML) has the potential to significantly aid medical practice. However, a recent article highlighted some negative consequences that may arise from using ML decision support in medicine. We argue here that whilst the concerns raised by the authors may be appropriate, they are not spe...

Descripción completa

Detalles Bibliográficos
Autores principales: McDonald, Laura, Ramagopalan, Sreeram V., Cox, Andrew P., Oguz, Mustafa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701440/
https://www.ncbi.nlm.nih.gov/pubmed/29250316
http://dx.doi.org/10.12688/f1000research.12693.1
_version_ 1783281341708632064
author McDonald, Laura
Ramagopalan, Sreeram V.
Cox, Andrew P.
Oguz, Mustafa
author_facet McDonald, Laura
Ramagopalan, Sreeram V.
Cox, Andrew P.
Oguz, Mustafa
author_sort McDonald, Laura
collection PubMed
description Machine learning (ML) has the potential to significantly aid medical practice. However, a recent article highlighted some negative consequences that may arise from using ML decision support in medicine. We argue here that whilst the concerns raised by the authors may be appropriate, they are not specific to ML, and thus the article may lead to an adverse perception about this technique in particular. Whilst ML is not without its limitations like any methodology, a balanced view is needed in order to not hamper its use in potentially enabling better patient care.
format Online
Article
Text
id pubmed-5701440
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher F1000 Research Limited
record_format MEDLINE/PubMed
spelling pubmed-57014402017-12-14 Unintended consequences of machine learning in medicine? McDonald, Laura Ramagopalan, Sreeram V. Cox, Andrew P. Oguz, Mustafa F1000Res Correspondence Machine learning (ML) has the potential to significantly aid medical practice. However, a recent article highlighted some negative consequences that may arise from using ML decision support in medicine. We argue here that whilst the concerns raised by the authors may be appropriate, they are not specific to ML, and thus the article may lead to an adverse perception about this technique in particular. Whilst ML is not without its limitations like any methodology, a balanced view is needed in order to not hamper its use in potentially enabling better patient care. F1000 Research Limited 2017-09-19 /pmc/articles/PMC5701440/ /pubmed/29250316 http://dx.doi.org/10.12688/f1000research.12693.1 Text en Copyright: © 2017 McDonald L et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Correspondence
McDonald, Laura
Ramagopalan, Sreeram V.
Cox, Andrew P.
Oguz, Mustafa
Unintended consequences of machine learning in medicine?
title Unintended consequences of machine learning in medicine?
title_full Unintended consequences of machine learning in medicine?
title_fullStr Unintended consequences of machine learning in medicine?
title_full_unstemmed Unintended consequences of machine learning in medicine?
title_short Unintended consequences of machine learning in medicine?
title_sort unintended consequences of machine learning in medicine?
topic Correspondence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701440/
https://www.ncbi.nlm.nih.gov/pubmed/29250316
http://dx.doi.org/10.12688/f1000research.12693.1
work_keys_str_mv AT mcdonaldlaura unintendedconsequencesofmachinelearninginmedicine
AT ramagopalansreeramv unintendedconsequencesofmachinelearninginmedicine
AT coxandrewp unintendedconsequencesofmachinelearninginmedicine
AT oguzmustafa unintendedconsequencesofmachinelearninginmedicine