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Cited by in F6Publishing
For: Liu D, Zhang X, Zheng T, Shi Q, Cui Y, Wang Y, Liu L. Optimisation and evaluation of the random forest model in the efficacy prediction of chemoradiotherapy for advanced cervical cancer based on radiomics signature from high-resolution T2 weighted images. Arch Gynecol Obstet 2021;303:811-20. [PMID: 33394142 DOI: 10.1007/s00404-020-05908-5] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Li H, Zhu M, Jian L, Bi F, Zhang X, Fang C, Wang Y, Wang J, Wu N, Yu X. Radiomic Score as a Potential Imaging Biomarker for Predicting Survival in Patients With Cervical Cancer. Front Oncol 2021;11:706043. [PMID: 34485139 DOI: 10.3389/fonc.2021.706043] [Reference Citation Analysis]
2 Scharl S, Hugo C, Weidenbächer CB, Bronger H, Brambs C, Kiechle M, Makowski MR, Combs SE, Schüttrumpf L. Intracavitary brachytherapy with additional Heyman capsules in the treatment of cervical cancer. Arch Gynecol Obstet 2022. [PMID: 35639163 DOI: 10.1007/s00404-022-06602-4] [Reference Citation Analysis]
3 Zhang H, Guo D, Liu H, He X, Qiao X, Liu X, Liu Y, Zhou J, Zhou Z, Liu X, Fang Z. MRI-Based Radiomics Models to Discriminate Hepatocellular Carcinoma and Non-Hepatocellular Carcinoma in LR-M According to LI-RADS Version 2018. Diagnostics 2022;12:1043. [DOI: 10.3390/diagnostics12051043] [Reference Citation Analysis]
4 Li XF, Huang YZ, Tang JY, Li RC, Wang XQ. Development of a random forest model for hypotension prediction after anesthesia induction for cardiac surgery. World J Clin Cases 2021; 9(29): 8729-8739 [PMID: 34734051 DOI: 10.12998/wjcc.v9.i29.8729] [Reference Citation Analysis]
5 Granata V, Coppola F, Grassi R, Fusco R, Tafuto S, Izzo F, Reginelli A, Maggialetti N, Buccicardi D, Frittoli B, Rengo M, Bortolotto C, Prost R, Lacasella GV, Montella M, Ciaghi E, Bellifemine F, De Muzio F, Danti G, Grazzini G, De Filippo M, Cappabianca S, Barresi C, Iafrate F, Stoppino LP, Laghi A, Grassi R, Brunese L, Neri E, Miele V, Faggioni L. Structured Reporting of Computed Tomography in the Staging of Neuroendocrine Neoplasms: A Delphi Consensus Proposal. Front Endocrinol 2021;12:748944. [DOI: 10.3389/fendo.2021.748944] [Reference Citation Analysis]