A deep learning-based semiautomated workflow for triaging follow-up MR scans in treated nasopharyngeal carcinoma-Reference-Cited by-同舟云学术

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A deep learning-based semiautomated workflow for triaging follow-up MR scans in treated nasopharyngeal carcinoma

Published:2023-12 Issue:12 Volume:26 Page:108347
ISSN:2589-0042
Container-title:iScience
language:en
Short-container-title:iScience

Author:

Huang Ying-Ying,Deng Yi-Shu,Liu Yang,Qiang Meng-Yun,Qiu Wen-Ze,Xia Wei-Xiong,Jing Bing-Zhong,Feng Chen-Yang,Chen Hao-Hua,Cao Xun,Zhou Jia-Yu,Huang Hao-Yang,Zhan Ze-Jiang,Deng Ying,Tang Lin-Quan,Mai Hai-Qiang,Sun Ying,Xie Chuan-Miao,Guo Xiang,Ke Liang-Ru,Lv Xing,Li Chao-Feng

Funder

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference41 articles.

1. Cancer Survivorship;Shapiro;N. Engl. J. Med.,2018

2. Local Cancer Recurrence: The Realities, Challenges, and Opportunities for New Therapies;Mahvi;CA A Cancer J. Clin.,2018

3. Cancer Statistics, 2021. CA;Siegel;Cancer J. Clin.,2021

4. Evolution of treatment for nasopharyngeal cancer – Success and setback in the intensity-modulated radiotherapy era;Lee;Radiother. Oncol.,2014

5. Intensity-modulated radiotherapy prolongs the survival of patients with nasopharyngeal carcinoma compared with conventional two-dimensional radiotherapy: A 10-year experience with a large cohort and long follow-up;Zhang;Eur. J. Cancer,2015

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