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Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics

Detalles Bibliográficos
Autores principales: Fang, Mengjie, Tian, Jie, Dong, Di
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9006631/
https://www.ncbi.nlm.nih.gov/pubmed/35434584
http://dx.doi.org/10.1016/j.eclinm.2022.101380
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author Fang, Mengjie
Tian, Jie
Dong, Di
author_facet Fang, Mengjie
Tian, Jie
Dong, Di
author_sort Fang, Mengjie
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spelling pubmed-90066312022-04-14 Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics Fang, Mengjie Tian, Jie Dong, Di EClinicalMedicine Comment Elsevier 2022-04-07 /pmc/articles/PMC9006631/ /pubmed/35434584 http://dx.doi.org/10.1016/j.eclinm.2022.101380 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Comment
Fang, Mengjie
Tian, Jie
Dong, Di
Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics
title Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics
title_full Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics
title_fullStr Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics
title_full_unstemmed Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics
title_short Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics
title_sort non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics
topic Comment
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9006631/
https://www.ncbi.nlm.nih.gov/pubmed/35434584
http://dx.doi.org/10.1016/j.eclinm.2022.101380
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