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Cited by in F6Publishing
For: Cao Y, Zhong X, Diao W, Mu J, Cheng Y, Jia Z. Radiomics in Differentiated Thyroid Cancer and Nodules: Explorations, Application, and Limitations. Cancers (Basel) 2021;13:2436. [PMID: 34069887 DOI: 10.3390/cancers13102436] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Zhu W, Huang X, Qi Q, Wu Z, Min X, Zhou A, Xu P. Artificial Neural Network-Based Ultrasound Radiomics Can Predict Large-Volume Lymph Node Metastasis in Clinical N0 Papillary Thyroid Carcinoma Patients. J Oncol 2022;2022:7133972. [PMID: 35756084 DOI: 10.1155/2022/7133972] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Wang Y, Zhang L, Qi L, Yi X, Li M, Zhou M, Chen D, Xiao Q, Wang C, Pang Y, Xu J, Deng H, Liu L, Guan X. Machine Learning: Applications and Advanced Progresses of Radiomics in Endocrine Neoplasms. J Oncol 2021;2021:8615450. [PMID: 34671399 DOI: 10.1155/2021/8615450] [Reference Citation Analysis]
3 Bini F, Pica A, Azzimonti L, Giusti A, Ruinelli L, Marinozzi F, Trimboli P. Artificial Intelligence in Thyroid Field-A Comprehensive Review. Cancers (Basel) 2021;13:4740. [PMID: 34638226 DOI: 10.3390/cancers13194740] [Reference Citation Analysis]