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Cited by in F6Publishing
For: Liu D, Chen J, Hu X, Yang K, Liu Y, Hu G, Ge H, Zhang W, Liu H. Imaging-Genomics in Glioblastoma: Combining Molecular and Imaging Signatures. Front Oncol 2021;11:699265. [PMID: 34295824 DOI: 10.3389/fonc.2021.699265] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Liu D, Chen J, Ge H, Yan Z, Luo B, Hu X, Yang K, Liu Y, Liu H, Zhang W. Radiogenomics to characterize the immune-related prognostic signature associated with biological functions in glioblastoma. Eur Radiol 2022. [PMID: 35881182 DOI: 10.1007/s00330-022-09012-x] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Saju AC, Chatterjee A, Sahu A, Gupta T, Krishnatry R, Mokal S, Sahay A, Epari S, Prasad M, Chinnaswamy G, Agarwal JP, Goda JS. Machine-learning approach to predict molecular subgroups of medulloblastoma using multiparametric MRI-based tumor radiomics. BJR 2022;95. [DOI: 10.1259/bjr.20211359] [Reference Citation Analysis]
3 Farzana W, Temtam AG, Shboul ZA, Rahman MM, Sadique MS, Iftekharuddin KM. Radiogenomic Prediction of MGMT Using Deep Learning with Bayesian Optimized Hyperparameters. Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries 2022. [DOI: 10.1007/978-3-031-09002-8_32] [Reference Citation Analysis]
4 Rahman MM, Sadique MS, Temtam AG, Farzana W, Vidyaratne L, Iftekharuddin KM. Brain Tumor Segmentation Using UNet-Context Encoding Network. Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries 2022. [DOI: 10.1007/978-3-031-08999-2_40] [Reference Citation Analysis]