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Journal Abstract Search

138 related items for PubMed ID: 32185138

  • 1. Identifying BAP1 Mutations in Clear-Cell Renal Cell Carcinoma by CT Radiomics: Preliminary Findings.
    Feng Z, Zhang L, Qi Z, Shen Q, Hu Z, Chen F.
    Front Oncol; 2020; 10():279. PubMed ID: 32185138
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  • 6. Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning-Based High-Dimensional Quantitative CT Texture Analysis in Predicting PBRM1 Mutation Status.
    Kocak B, Durmaz ES, Ates E, Ulusan MB.
    AJR Am J Roentgenol; 2019 Mar; 212(3):W55-W63. PubMed ID: 30601030
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  • 8. Development of unenhanced CT-based imaging signature for BAP1 mutation status prediction in malignant pleural mesothelioma: Consideration of 2D and 3D segmentation.
    Xie XJ, Liu SY, Chen JY, Zhao Y, Jiang J, Wu L, Zhang XW, Wu Y, Duan H, He B, Luo H, Han D.
    Lung Cancer; 2021 Jul; 157():30-39. PubMed ID: 34052706
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  • 11. Advancements in Radiogenomics for Clear Cell Renal Cell Carcinoma: Understanding the Impact of BAP1 Mutation.
    Greco F, D'Andrea V, Buoso A, Cea L, Bernetti C, Beomonte Zobel B, Mallio CA.
    J Clin Med; 2024 Jul 06; 13(13):. PubMed ID: 38999524
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  • 13. Noninvasive Fuhrman grading of clear cell renal cell carcinoma using computed tomography radiomic features and machine learning.
    Nazari M, Shiri I, Hajianfar G, Oveisi N, Abdollahi H, Deevband MR, Oveisi M, Zaidi H.
    Radiol Med; 2020 Aug 06; 125(8):754-762. PubMed ID: 32193870
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  • 14. A BAP1 Mutation-specific MicroRNA Signature Predicts Clinical Outcomes in Clear Cell Renal Cell Carcinoma Patients with Wild-type BAP1.
    Ge YZ, Xu LW, Zhou CC, Lu TZ, Yao WT, Wu R, Zhao YC, Xu X, Hu ZK, Wang M, Yang XB, Zhou LH, Zhong B, Xu Z, Li WC, Zhu JG, Jia RP.
    J Cancer; 2017 Aug 06; 8(13):2643-2652. PubMed ID: 28900502
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  • 17. Bap1 is essential for kidney function and cooperates with Vhl in renal tumorigenesis.
    Wang SS, Gu YF, Wolff N, Stefanius K, Christie A, Dey A, Hammer RE, Xie XJ, Rakheja D, Pedrosa I, Carroll T, McKay RM, Kapur P, Brugarolas J.
    Proc Natl Acad Sci U S A; 2014 Nov 18; 111(46):16538-43. PubMed ID: 25359211
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  • 18. Differentiation of fat-poor angiomyolipoma from clear cell renal cell carcinoma in contrast-enhanced MDCT images using quantitative feature classification.
    Lee HS, Hong H, Jung DC, Park S, Kim J.
    Med Phys; 2017 Jul 18; 44(7):3604-3614. PubMed ID: 28376281
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  • 19. A Computed Tomography-Based Radiomics Nomogram to Preoperatively Predict Tumor Necrosis in Patients With Clear Cell Renal Cell Carcinoma.
    Jiang Y, Li W, Huang C, Tian C, Chen Q, Zeng X, Cao Y, Chen Y, Yang Y, Liu H, Bo Y, Luo C, Li Y, Zhang T, Wang R.
    Front Oncol; 2020 Jul 18; 10():592. PubMed ID: 32547934
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  • 20. Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.
    Gu Q, Feng Z, Liang Q, Li M, Deng J, Ma M, Wang W, Liu J, Liu P, Rong P.
    Eur J Radiol; 2019 Sep 18; 118():32-37. PubMed ID: 31439255
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