Machine learning reveals salivary glycopatterns as potential biomarkers for the diagnosis and prognosis of papillary thyroid cancer-Reference-Cited by-同舟云学术

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Machine learning reveals salivary glycopatterns as potential biomarkers for the diagnosis and prognosis of papillary thyroid cancer

Published:2022-08 Issue: Volume:215 Page:280-289
ISSN:0141-8130
Container-title:International Journal of Biological Macromolecules
language:en
Short-container-title:International Journal of Biological Macromolecules

Author:

Ren Xiameng,Shu Jian,Wang Junhong,Guo Yonghong,Zhang Ying,Yue Lixin,Yu Hanjie,Chen Wentian,Zhang Chen,Ma Jiancang,Li Zheng

Funder

Natural Science Foundation of Shaanxi Province

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Elsevier BV

Subject

Molecular Biology,General Medicine,Biochemistry,Structural Biology

Reference44 articles.

1. The changing landscape of papillary thyroid cancer: epidemiology, management, and the implications for patients[J];Lubitz;Cancer,2016

2. Thyroid cancer[J];Cabanillas;Lancet,2016

3. N-glycan profiling of papillary thyroid carcinoma tissues by MALDI-TOF-MS[J];Koçak;Anal. Biochem.,2019

4. The accuracy of thyroid nodule ultrasound to predict thyroid cancer: systematic review and meta-analysis[J];Brito;J. Clin. Endocrinol. Metab.,2014

5. 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: the American Thyroid Association guidelines task force on thyroid nodules and differentiated thyroid cancer[J];Haugen;Thyroid,2016

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