A deep learning MRI-based signature may provide risk-stratification strategies for nasopharyngeal carcinoma-Reference-Cited by-同舟云学术

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A deep learning MRI-based signature may provide risk-stratification strategies for nasopharyngeal carcinoma

Published:2023-06-26 Issue:11 Volume:280 Page:5039-5047
ISSN:0937-4477
Container-title:European Archives of Oto-Rhino-Laryngology
language:en
Short-container-title:Eur Arch Otorhinolaryngol

Author:

Yang Chen,Chen Yuan,Zhu Luchao,Wang Liansheng,Lin Qin^ORCID

Funder

Natural Science Foundation of Fujian Province

National Natural Science Foundation of China

Key Medical and Health Projects in Xiamen

Publisher

Springer Science and Business Media LLC

Subject

General Medicine,Otorhinolaryngology

Link

https://link.springer.com/content/pdf/10.1007/s00405-023-08084-9.pdf

Reference41 articles.

1. Tang LL, Chen WQ, Xue WQ et al (2016) Global trends in incidence and mortality of nasopharyngeal carcinoma. Cancer Lett 374(1):22–30

2. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68(6):394–424

3. Chen YP, Chan ATC, Le QT, Blanchard P, Sun Y, Ma J (2019) Nasopharyngeal carcinoma. Lancet 394(10192):64–80

4. Pan JJ, Ng WT, Zong JF et al (2016) Prognostic nomogram for refining the prognostication of the proposed 8th edition of the AJCC/UICC staging system for nasopharyngeal cancer in the era of intensity-modulated radiotherapy. Cancer 122(21):3307–3315

5. Wong KCW, Hui EP, Lo KW et al (2021) Nasopharyngeal carcinoma: an evolving paradigm. Nat Rev Clin Oncol 18(11):679–695

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