Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans

Cho et al. use a radiomics-guided deep-learning approach to model the prognosis of lung adenocarcinoma from CT scan data. This study demonstrates the utility of this technology as a predictive approach for stratifying clinical prognostic groups.

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Autores principales:	Hwan-ho Cho, Ho Yun Lee, Eunjin Kim, Geewon Lee, Jonghoon Kim, Junmo Kwon, Hyunjin Park
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/e3df764d36224d0dbccb596f1c5bbbad
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

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spelling	oai:doaj.org-article:e3df764d36224d0dbccb596f1c5bbbad2021-11-14T12:12:06ZRadiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans10.1038/s42003-021-02814-72399-3642https://doaj.org/article/e3df764d36224d0dbccb596f1c5bbbad2021-11-01T00:00:00Zhttps://doi.org/10.1038/s42003-021-02814-7https://doaj.org/toc/2399-3642Cho et al. use a radiomics-guided deep-learning approach to model the prognosis of lung adenocarcinoma from CT scan data. This study demonstrates the utility of this technology as a predictive approach for stratifying clinical prognostic groups.Hwan-ho ChoHo Yun LeeEunjin KimGeewon LeeJonghoon KimJunmo KwonHyunjin ParkNature PortfolioarticleBiology (General)QH301-705.5ENCommunications Biology, Vol 4, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Hwan-ho Cho Ho Yun Lee Eunjin Kim Geewon Lee Jonghoon Kim Junmo Kwon Hyunjin Park Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans
description	Cho et al. use a radiomics-guided deep-learning approach to model the prognosis of lung adenocarcinoma from CT scan data. This study demonstrates the utility of this technology as a predictive approach for stratifying clinical prognostic groups.
format	article
author	Hwan-ho Cho Ho Yun Lee Eunjin Kim Geewon Lee Jonghoon Kim Junmo Kwon Hyunjin Park
author_facet	Hwan-ho Cho Ho Yun Lee Eunjin Kim Geewon Lee Jonghoon Kim Junmo Kwon Hyunjin Park
author_sort	Hwan-ho Cho
title	Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans
title_short	Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans
title_full	Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans
title_fullStr	Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans
title_full_unstemmed	Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans
title_sort	radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from ct scans
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/e3df764d36224d0dbccb596f1c5bbbad
work_keys_str_mv	AT hwanhocho radiomicsguideddeepneuralnetworksstratifylungadenocarcinomaprognosisfromctscans AT hoyunlee radiomicsguideddeepneuralnetworksstratifylungadenocarcinomaprognosisfromctscans AT eunjinkim radiomicsguideddeepneuralnetworksstratifylungadenocarcinomaprognosisfromctscans AT geewonlee radiomicsguideddeepneuralnetworksstratifylungadenocarcinomaprognosisfromctscans AT jonghoonkim radiomicsguideddeepneuralnetworksstratifylungadenocarcinomaprognosisfromctscans AT junmokwon radiomicsguideddeepneuralnetworksstratifylungadenocarcinomaprognosisfromctscans AT hyunjinpark radiomicsguideddeepneuralnetworksstratifylungadenocarcinomaprognosisfromctscans
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Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans

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