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Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan

Detalles Bibliográficos
Autores principales: Chang, Chao-Chun, Tang, En-Kuei, Wei, Yu-Feng, Lin, Chia-Ying, Wu, Fu-Zong, Wu, Ming-Ting, Liu, Yi-Sheng, Yen, Yi-Ting, Ma, Mi-Chia, Tseng, Yau-Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266095/
https://www.ncbi.nlm.nih.gov/pubmed/37324009
http://dx.doi.org/10.3389/fonc.2023.1220962
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author Chang, Chao-Chun
Tang, En-Kuei
Wei, Yu-Feng
Lin, Chia-Ying
Wu, Fu-Zong
Wu, Ming-Ting
Liu, Yi-Sheng
Yen, Yi-Ting
Ma, Mi-Chia
Tseng, Yau-Lin
author_facet Chang, Chao-Chun
Tang, En-Kuei
Wei, Yu-Feng
Lin, Chia-Ying
Wu, Fu-Zong
Wu, Ming-Ting
Liu, Yi-Sheng
Yen, Yi-Ting
Ma, Mi-Chia
Tseng, Yau-Lin
author_sort Chang, Chao-Chun
collection PubMed
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spelling pubmed-102660952023-06-15 Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan Chang, Chao-Chun Tang, En-Kuei Wei, Yu-Feng Lin, Chia-Ying Wu, Fu-Zong Wu, Ming-Ting Liu, Yi-Sheng Yen, Yi-Ting Ma, Mi-Chia Tseng, Yau-Lin Front Oncol Oncology Frontiers Media S.A. 2023-05-31 /pmc/articles/PMC10266095/ /pubmed/37324009 http://dx.doi.org/10.3389/fonc.2023.1220962 Text en Copyright © 2023 Chang, Tang, Wei, Lin, Wu, Wu, Liu, Yen, Ma and Tseng https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Chang, Chao-Chun
Tang, En-Kuei
Wei, Yu-Feng
Lin, Chia-Ying
Wu, Fu-Zong
Wu, Ming-Ting
Liu, Yi-Sheng
Yen, Yi-Ting
Ma, Mi-Chia
Tseng, Yau-Lin
Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan
title Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan
title_full Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan
title_fullStr Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan
title_full_unstemmed Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan
title_short Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan
title_sort corrigendum: clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266095/
https://www.ncbi.nlm.nih.gov/pubmed/37324009
http://dx.doi.org/10.3389/fonc.2023.1220962
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