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Journal Abstract Search

184 related items for PubMed ID: 35249531

  • 1. Contrast-enhanced CT-based radiomics model for differentiating risk subgroups of thymic epithelial tumors.
    Yu C, Li T, Yang X, Zhang R, Xin L, Zhao Z, Cui J.
    BMC Med Imaging; 2022 Mar 06; 22(1):37. PubMed ID: 35249531
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  • 2. Optimizing the radiomics-machine-learning model based on non-contrast enhanced CT for the simplified risk categorization of thymic epithelial tumors: A large cohort retrospective study.
    Feng XL, Wang SZ, Chen HH, Huang YX, Xin YK, Zhang T, Cheng DL, Mao L, Li XL, Liu CX, Hu YC, Wang W, Cui GB, Nan HY.
    Lung Cancer; 2022 Apr 06; 166():150-160. PubMed ID: 35287067
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  • 6. Development and validation of a deep learning radiomics nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes.
    Chen X, Feng B, Xu K, Chen Y, Duan X, Jin Z, Li K, Li R, Long W, Liu X.
    Eur Radiol; 2023 Oct 06; 33(10):6804-6816. PubMed ID: 37148352
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  • 7. Radiomics Analysis of Multiphasic Computed Tomography Images for Distinguishing High-Risk Thymic Epithelial Tumors From Low-Risk Thymic Epithelial Tumors.
    Liufu Y, Wen Y, Wu W, Su R, Liu S, Li J, Pan X, Chen K, Guan Y.
    J Comput Assist Tomogr; 2023 Oct 06; 47(2):220-228. PubMed ID: 36877755
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  • 9. Diagnostic and prognostic values of 2-[18F]FDG PET/CT in resectable thymic epithelial tumour.
    Han S, Kim YI, Oh JS, Seo SY, Park MJ, Lee GD, Choi S, Kim HR, Kim YH, Kim DK, Park SI, Ryu JS.
    Eur Radiol; 2022 Feb 06; 32(2):1173-1183. PubMed ID: 34448035
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  • 10. Differentiating the grades of thymic epithelial tumor malignancy using textural features of intratumoral heterogeneity via (18)F-FDG PET/CT.
    Lee HS, Oh JS, Park YS, Jang SJ, Choi IS, Ryu JS.
    Ann Nucl Med; 2016 May 06; 30(4):309-19. PubMed ID: 26868139
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  • 12. Dual-energy CT perfusion imaging for differentiating WHO subtypes of thymic epithelial tumors.
    Yu C, Li T, Zhang R, Yang X, Yang Z, Xin L, Zhao Z.
    Sci Rep; 2020 Mar 26; 10(1):5511. PubMed ID: 32218504
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  • 14. Development and Validation of Contrast-Enhanced CT-Based Deep Transfer Learning and Combined Clinical-Radiomics Model to Discriminate Thymomas and Thymic Cysts: A Multicenter Study.
    Yang Y, Cheng J, Peng Z, Yi L, Lin Z, He A, Jin M, Cui C, Liu Y, Zhong Q, Zuo M.
    Acad Radiol; 2024 Apr 26; 31(4):1615-1628. PubMed ID: 37949702
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  • 17. Predicting pathological subtypes and stages of thymic epithelial tumors using DWI: value of combining ADC and texture parameters.
    Li B, Xin YK, Xiao G, Li GF, Duan SJ, Han Y, Feng XL, Yan WQ, Rong WC, Wang SM, Hu YC, Cui GB.
    Eur Radiol; 2019 Oct 26; 29(10):5330-5340. PubMed ID: 30877464
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  • 18. Does CT of thymic epithelial tumors enable us to differentiate histologic subtypes and predict prognosis?
    Jeong YJ, Lee KS, Kim J, Shim YM, Han J, Kwon OJ.
    AJR Am J Roentgenol; 2004 Aug 26; 183(2):283-9. PubMed ID: 15269013
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  • 19. The role of Tc-99m-2-Methoxy-Isobutyl-Isonitrile Single Photon Emission Computed Tomography in visualizing anterior mediastinal tumor and differentiating histologic type of thymoma.
    Fiorelli A, Vicidomini G, Laperuta P, Rambaldi P, Mansi L, Rotondo A, Santini M.
    Eur J Cardiothorac Surg; 2011 Jul 26; 40(1):136-42. PubMed ID: 21273088
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