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Cited by in F6Publishing
For: Huang G, Cui Y, Wang P, Ren J, Wang L, Ma Y, Jia Y, Ma X, Zhao L. Multi-Parametric Magnetic Resonance Imaging-Based Radiomics Analysis of Cervical Cancer for Preoperative Prediction of Lymphovascular Space Invasion. Front Oncol 2021;11:663370. [PMID: 35096556 DOI: 10.3389/fonc.2021.663370] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Wang W, Fan X, Yang J, Wang X, Gu Y, Chen M, Jiang Y, Liu L, Zhang M. Preliminary MRI Study of Extracellular Volume Fraction for Identification of Lymphovascular Space Invasion of Cervical Cancer. J Magn Reson Imaging 2023;57:587-97. [PMID: 36094153 DOI: 10.1002/jmri.28423] [Reference Citation Analysis]
2 Ou Z, Mao W, Tan L, Yang Y, Liu S, Zhang Y, Li B, Zhao D. Prediction of Postoperative Pathologic Risk Factors in Cervical Cancer Patients Treated with Radical Hysterectomy by Machine Learning. Curr Oncol 2022;29:9613-29. [PMID: 36547169 DOI: 10.3390/curroncol29120755] [Reference Citation Analysis]
3 Song Q, Tian S, Ma C, Meng X, Chen L, Wang N, Lin L, Wang J, Song Q, Liu A. Amide proton transfer weighted imaging combined with dynamic contrast-enhanced MRI in predicting lymphovascular space invasion and deep stromal invasion of IB1-IIA1 cervical cancer. Front Oncol 2022;12:916846. [DOI: 10.3389/fonc.2022.916846] [Reference Citation Analysis]