Cargando…

Machine learning in oncology: a review

Machine learning is a set of techniques that promise to greatly enhance our data-processing capability. In the field of oncology, ML presents itself with a wealth of possible applications to the research and the clinical context, such as automated diagnosis and precise treatment modulation. In this...

Descripción completa

Detalles Bibliográficos
Autor principal: Nardini, Cecilia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cancer Intelligence 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7373638/
https://www.ncbi.nlm.nih.gov/pubmed/32728381
http://dx.doi.org/10.3332/ecancer.2020.1065
_version_ 1783561534283186176
author Nardini, Cecilia
author_facet Nardini, Cecilia
author_sort Nardini, Cecilia
collection PubMed
description Machine learning is a set of techniques that promise to greatly enhance our data-processing capability. In the field of oncology, ML presents itself with a wealth of possible applications to the research and the clinical context, such as automated diagnosis and precise treatment modulation. In this paper, we will review the principal applications of ML techniques in oncology and explore in detail how they work. This will allow us to discuss the issues and challenges that ML faces in this field, and ultimately gain a greater understanding of ML techniques and how they can improve oncological research and practice.
format Online
Article
Text
id pubmed-7373638
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Cancer Intelligence
record_format MEDLINE/PubMed
spelling pubmed-73736382020-07-28 Machine learning in oncology: a review Nardini, Cecilia Ecancermedicalscience Review Machine learning is a set of techniques that promise to greatly enhance our data-processing capability. In the field of oncology, ML presents itself with a wealth of possible applications to the research and the clinical context, such as automated diagnosis and precise treatment modulation. In this paper, we will review the principal applications of ML techniques in oncology and explore in detail how they work. This will allow us to discuss the issues and challenges that ML faces in this field, and ultimately gain a greater understanding of ML techniques and how they can improve oncological research and practice. Cancer Intelligence 2020-06-30 /pmc/articles/PMC7373638/ /pubmed/32728381 http://dx.doi.org/10.3332/ecancer.2020.1065 Text en © the authors; licensee ecancermedicalscience. http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Nardini, Cecilia
Machine learning in oncology: a review
title Machine learning in oncology: a review
title_full Machine learning in oncology: a review
title_fullStr Machine learning in oncology: a review
title_full_unstemmed Machine learning in oncology: a review
title_short Machine learning in oncology: a review
title_sort machine learning in oncology: a review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7373638/
https://www.ncbi.nlm.nih.gov/pubmed/32728381
http://dx.doi.org/10.3332/ecancer.2020.1065
work_keys_str_mv AT nardinicecilia machinelearninginoncologyareview