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Cited by in F6Publishing
For: Ekert K, Hinterleitner C, Baumgartner K, Fritz J, Horger M. Extended Texture Analysis of Non-Enhanced Whole-Body MRI Image Data for Response Assessment in Multiple Myeloma Patients Undergoing Systemic Therapy. Cancers (Basel). 2020;12. [PMID: 32213834 DOI: 10.3390/cancers12030761] [Cited by in Crossref: 13] [Cited by in F6Publishing: 10] [Article Influence: 13.0] [Reference Citation Analysis]
Number Citing Articles
1 Huang Y, Zeng H, Chen L, Luo Y, Ma X, Zhao Y. Exploration of an Integrative Prognostic Model of Radiogenomics Features With Underlying Gene Expression Patterns in Clear Cell Renal Cell Carcinoma. Front Oncol 2021;11:640881. [PMID: 33763374 DOI: 10.3389/fonc.2021.640881] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Xiong X, Wang J, Hu S, Dai Y, Zhang Y, Hu C. Differentiating Between Multiple Myeloma and Metastasis Subtypes of Lumbar Vertebra Lesions Using Machine Learning-Based Radiomics. Front Oncol. 2021;11:601699. [PMID: 33718148 DOI: 10.3389/fonc.2021.601699] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
3 Tagliafico AS, Dominietto A, Belgioia L, Campi C, Schenone D, Piana M. Quantitative Imaging and Radiomics in Multiple Myeloma: A Potential Opportunity? Medicina (Kaunas). 2021;57. [PMID: 33494449 DOI: 10.3390/medicina57020094] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Tagliafico AS. Imaging in multiple myeloma: Computed tomography or magnetic resonance imaging? World J Radiol 2021; 13(7): 223-226 [PMID: 34367508 DOI: 10.4329/wjr.v13.i7.223] [Reference Citation Analysis]
5 Li H, Xie Y, Liu H, Wang X. Non-Contrast CT-Based Radiomics Score for Predicting Hematoma Enlargement in Spontaneous Intracerebral Hemorrhage. Clin Neuroradiol 2021. [PMID: 34324004 DOI: 10.1007/s00062-021-01062-w] [Reference Citation Analysis]
6 Chen X, Sheikh K, Nakajima E, Lin CT, Lee J, Hu C, Hales RK, Forde PM, Naidoo J, Voong KR. Radiation Versus Immune Checkpoint Inhibitor Associated Pneumonitis: Distinct Radiologic Morphologies. Oncologist 2021. [PMID: 34251728 DOI: 10.1002/onco.13900] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
7 Zhang B, Bian B, Zhao Z, Lin F, Zhu Z, Lou M. Correlations between apparent diffusion coefficient values of WB-DWI and clinical parameters in multiple myeloma. BMC Med Imaging 2021;21:98. [PMID: 34103001 DOI: 10.1186/s12880-021-00631-2] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
8 Fan Z, Sun Z, Fang S, Li Y, Liu X, Liang Y, Liu Y, Zhou C, Zhu Q, Zhang H, Li T, Li S, Jiang T, Wang Y, Wang L. Preoperative Radiomics Analysis of 1p/19q Status in WHO Grade II Gliomas. Front Oncol 2021;11:616740. [PMID: 34295805 DOI: 10.3389/fonc.2021.616740] [Reference Citation Analysis]
9 Hameed M, Sandhu A, Soneji N, Amiras D, Rockall A, Messiou C, Wallitt K, Barwick TD. Pictorial review of whole body MRI in myeloma: emphasis on diffusion-weighted imaging. Br J Radiol 2020;93:20200312. [PMID: 32667830 DOI: 10.1259/bjr.20200312] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 Liu J, Zeng P, Guo W, Wang C, Geng Y, Lang N, Yuan H. Prediction of High-Risk Cytogenetic Status in Multiple Myeloma Based on Magnetic Resonance Imaging: Utility of Radiomics and Comparison of Machine Learning Methods. J Magn Reson Imaging 2021. [PMID: 33979466 DOI: 10.1002/jmri.27637] [Cited by in F6Publishing: 1] [Reference Citation Analysis]