Cargando…
Structural neuroimaging as clinical predictor: A review of machine learning applications
In this paper, we provide an extensive overview of machine learning techniques applied to structural magnetic resonance imaging (MRI) data to obtain clinical classifiers. We specifically address practical problems commonly encountered in the literature, with the aim of helping researchers improve th...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6108077/ https://www.ncbi.nlm.nih.gov/pubmed/30167371 http://dx.doi.org/10.1016/j.nicl.2018.08.019 |
_version_ | 1783350082335145984 |
---|---|
author | Mateos-Pérez, José María Dadar, Mahsa Lacalle-Aurioles, María Iturria-Medina, Yasser Zeighami, Yashar Evans, Alan C. |
author_facet | Mateos-Pérez, José María Dadar, Mahsa Lacalle-Aurioles, María Iturria-Medina, Yasser Zeighami, Yashar Evans, Alan C. |
author_sort | Mateos-Pérez, José María |
collection | PubMed |
description | In this paper, we provide an extensive overview of machine learning techniques applied to structural magnetic resonance imaging (MRI) data to obtain clinical classifiers. We specifically address practical problems commonly encountered in the literature, with the aim of helping researchers improve the application of these techniques in future works. Additionally, we survey how these algorithms are applied to a wide range of diseases and disorders (e.g. Alzheimer's disease (AD), Parkinson's disease (PD), autism, multiple sclerosis, traumatic brain injury, etc.) in order to provide a comprehensive view of the state of the art in different fields. |
format | Online Article Text |
id | pubmed-6108077 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-61080772018-08-30 Structural neuroimaging as clinical predictor: A review of machine learning applications Mateos-Pérez, José María Dadar, Mahsa Lacalle-Aurioles, María Iturria-Medina, Yasser Zeighami, Yashar Evans, Alan C. Neuroimage Clin Regular Article In this paper, we provide an extensive overview of machine learning techniques applied to structural magnetic resonance imaging (MRI) data to obtain clinical classifiers. We specifically address practical problems commonly encountered in the literature, with the aim of helping researchers improve the application of these techniques in future works. Additionally, we survey how these algorithms are applied to a wide range of diseases and disorders (e.g. Alzheimer's disease (AD), Parkinson's disease (PD), autism, multiple sclerosis, traumatic brain injury, etc.) in order to provide a comprehensive view of the state of the art in different fields. Elsevier 2018-08-10 /pmc/articles/PMC6108077/ /pubmed/30167371 http://dx.doi.org/10.1016/j.nicl.2018.08.019 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Regular Article Mateos-Pérez, José María Dadar, Mahsa Lacalle-Aurioles, María Iturria-Medina, Yasser Zeighami, Yashar Evans, Alan C. Structural neuroimaging as clinical predictor: A review of machine learning applications |
title | Structural neuroimaging as clinical predictor: A review of machine learning applications |
title_full | Structural neuroimaging as clinical predictor: A review of machine learning applications |
title_fullStr | Structural neuroimaging as clinical predictor: A review of machine learning applications |
title_full_unstemmed | Structural neuroimaging as clinical predictor: A review of machine learning applications |
title_short | Structural neuroimaging as clinical predictor: A review of machine learning applications |
title_sort | structural neuroimaging as clinical predictor: a review of machine learning applications |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6108077/ https://www.ncbi.nlm.nih.gov/pubmed/30167371 http://dx.doi.org/10.1016/j.nicl.2018.08.019 |
work_keys_str_mv | AT mateosperezjosemaria structuralneuroimagingasclinicalpredictorareviewofmachinelearningapplications AT dadarmahsa structuralneuroimagingasclinicalpredictorareviewofmachinelearningapplications AT lacalleauriolesmaria structuralneuroimagingasclinicalpredictorareviewofmachinelearningapplications AT iturriamedinayasser structuralneuroimagingasclinicalpredictorareviewofmachinelearningapplications AT zeighamiyashar structuralneuroimagingasclinicalpredictorareviewofmachinelearningapplications AT evansalanc structuralneuroimagingasclinicalpredictorareviewofmachinelearningapplications |