Machine learning for tissue diagnostics in oncology: brave new world

Machine learning is an exciting technology with broad application in big data analysis, as well as increasingly in specialised healthcare. As a diagnostic tool in tissue workup and pathology, it has the potential for personalised and stratified approaches, but the limitations and pitfalls need to be...

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Detalles Bibliográficos
Autor principal: Halama, Niels
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Editorial
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6738066/
https://www.ncbi.nlm.nih.gov/pubmed/31395951
http://dx.doi.org/10.1038/s41416-019-0535-1
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author Halama, Niels
author_facet Halama, Niels
author_sort Halama, Niels
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description Machine learning is an exciting technology with broad application in big data analysis, as well as increasingly in specialised healthcare. As a diagnostic tool in tissue workup and pathology, it has the potential for personalised and stratified approaches, but the limitations and pitfalls need to be better understood and characterised especially in this critical area of medical care.
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spelling pubmed-67380662019-09-12 Machine learning for tissue diagnostics in oncology: brave new world Halama, Niels Br J Cancer Editorial Machine learning is an exciting technology with broad application in big data analysis, as well as increasingly in specialised healthcare. As a diagnostic tool in tissue workup and pathology, it has the potential for personalised and stratified approaches, but the limitations and pitfalls need to be better understood and characterised especially in this critical area of medical care. Nature Publishing Group UK 2019-08-09 2019-09-10 /pmc/articles/PMC6738066/ /pubmed/31395951 http://dx.doi.org/10.1038/s41416-019-0535-1 Text en © The Author(s) 2019 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Editorial
Halama, Niels
Machine learning for tissue diagnostics in oncology: brave new world
title Machine learning for tissue diagnostics in oncology: brave new world
title_full Machine learning for tissue diagnostics in oncology: brave new world
title_fullStr Machine learning for tissue diagnostics in oncology: brave new world
title_full_unstemmed Machine learning for tissue diagnostics in oncology: brave new world
title_short Machine learning for tissue diagnostics in oncology: brave new world
title_sort machine learning for tissue diagnostics in oncology: brave new world
topic Editorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6738066/
https://www.ncbi.nlm.nih.gov/pubmed/31395951
http://dx.doi.org/10.1038/s41416-019-0535-1
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