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315 related items for PubMed ID: 31822969

  • 1. Texture analysis and machine learning algorithms accurately predict histologic grade in small (< 4 cm) clear cell renal cell carcinomas: a pilot study.
    Haji-Momenian S, Lin Z, Patel B, Law N, Michalak A, Nayak A, Earls J, Loew M.
    Abdom Radiol (NY); 2020 Mar; 45(3):789-798. PubMed ID: 31822969
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  • 3. Clear cell renal cell carcinoma: Machine learning-based computed tomography radiomics analysis for the prediction of WHO/ISUP grade.
    Shu J, Wen D, Xi Y, Xia Y, Cai Z, Xu W, Meng X, Liu B, Yin H.
    Eur J Radiol; 2019 Dec; 121():108738. PubMed ID: 31756634
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  • 5. 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; 125(8):754-762. PubMed ID: 32193870
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  • 10. Texture analysis of small renal cell carcinomas at MDCT for predicting relevant histologic and protein biomarkers.
    Scrima AT, Lubner MG, Abel EJ, Havighurst TC, Shapiro DD, Huang W, Pickhardt PJ.
    Abdom Radiol (NY); 2019 Jun; 44(6):1999-2008. PubMed ID: 29804215
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  • 12. Clear Cell Renal Cell Carcinoma: Machine Learning-Based Quantitative Computed Tomography Texture Analysis for Prediction of Fuhrman Nuclear Grade.
    Bektas CT, Kocak B, Yardimci AH, Turkcanoglu MH, Yucetas U, Koca SB, Erdim C, Kilickesmez O.
    Eur Radiol; 2019 Mar; 29(3):1153-1163. PubMed ID: 30167812
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  • 14. CT Textural Analysis of Large Primary Renal Cell Carcinomas: Pretreatment Tumor Heterogeneity Correlates With Histologic Findings and Clinical Outcomes.
    Lubner MG, Stabo N, Abel EJ, Del Rio AM, Pickhardt PJ.
    AJR Am J Roentgenol; 2016 Jul; 207(1):96-105. PubMed ID: 27145377
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  • 16. The value of quantitative CT texture analysis in differentiation of angiomyolipoma without visible fat from clear cell renal cell carcinoma on four-phase contrast-enhanced CT images.
    You MW, Kim N, Choi HJ.
    Clin Radiol; 2019 Jul; 74(7):547-554. PubMed ID: 31010583
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  • 17. Radiomics of small renal masses on multiphasic CT: accuracy of machine learning-based classification models for the differentiation of renal cell carcinoma and angiomyolipoma without visible fat.
    Yang R, Wu J, Sun L, Lai S, Xu Y, Liu X, Ma Y, Zhen X.
    Eur Radiol; 2020 Feb; 30(2):1254-1263. PubMed ID: 31468159
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  • 19. Deep learning and radiomics: the utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT.
    Coy H, Hsieh K, Wu W, Nagarajan MB, Young JR, Douek ML, Brown MS, Scalzo F, Raman SS.
    Abdom Radiol (NY); 2019 Jun; 44(6):2009-2020. PubMed ID: 30778739
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