BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

151 related articles for article (PubMed ID: 36396624)

  • 1. Prediction of pathological staging and grading of renal clear cell carcinoma based on deep learning algorithms.
    Wen-Zhi G; Tai T; Zhixin F; Huanyu L; Yanqing G; Yuexian G; Xuesong L
    J Int Med Res; 2022 Nov; 50(11):3000605221135163. PubMed ID: 36396624
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Novel Preoperative Prediction Model Based on Deep Learning to Predict Neoplasm T Staging and Grading in Patients with Upper Tract Urothelial Carcinoma.
    He Y; Gao W; Ying W; Feng N; Wang Y; Jiang P; Gong Y; Li X
    J Clin Med; 2022 Sep; 11(19):. PubMed ID: 36233682
    [No Abstract]   [Full Text] [Related]  

  • 3. A CT-based deep learning model for predicting the nuclear grade of clear cell renal cell carcinoma.
    Lin F; Ma C; Xu J; Lei Y; Li Q; Lan Y; Sun M; Long W; Cui E
    Eur J Radiol; 2020 Aug; 129():109079. PubMed ID: 32526669
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Characterization of renal artery variation in patients with clear cell renal cell carcinoma and the predictive value of accessory renal artery in pathological grading of renal cell carcinoma: a retrospective and observational study.
    Lv D; Zhou H; Cui F; Wen J; Shuang W
    BMC Cancer; 2023 Mar; 23(1):274. PubMed ID: 36966274
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep learning using contrast-enhanced ultrasound images to predict the nuclear grade of clear cell renal cell carcinoma.
    Bai Y; An ZC; Li F; Du LF; Xie TW; Zhang XP; Cai YY
    World J Urol; 2024 Mar; 42(1):184. PubMed ID: 38512539
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Multimodal deep learning for personalized renal cell carcinoma prognosis: Integrating CT imaging and clinical data.
    Mahootiha M; Qadir HA; Bergsland J; Balasingham I
    Comput Methods Programs Biomed; 2024 Feb; 244():107978. PubMed ID: 38113804
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Development and validation of a CT-based nomogram for preoperative prediction of clear cell renal cell carcinoma grades.
    Zheng Z; Chen Z; Xie Y; Zhong Q; Xie W
    Eur Radiol; 2021 Aug; 31(8):6078-6086. PubMed ID: 33515086
    [TBL] [Abstract][Full Text] [Related]  

  • 9. The 'Stage, Size, Grade and Necrosis' score is more accurate than the University of California Los Angeles Integrated Staging System for predicting cancer-specific survival in patients with clear cell renal cell carcinoma.
    Ficarra V; Novara G; Galfano A; Brunelli M; Cavalleri S; Martignoni G; Artibani W
    BJU Int; 2009 Jan; 103(2):165-70. PubMed ID: 18782313
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Can texture analysis based on single unenhanced CT accurately predict the WHO/ISUP grading of localized clear cell renal cell carcinoma?
    Wang X; Song G; Jiang H; Zheng L; Pang P; Xu J
    Abdom Radiol (NY); 2021 Sep; 46(9):4289-4300. PubMed ID: 33909090
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Architectural Patterns are a Relevant Morphologic Grading System for Clear Cell Renal Cell Carcinoma Prognosis Assessment: Comparisons With WHO/ISUP Grade and Integrated Staging Systems.
    Verine J; Colin D; Nheb M; Prapotnich D; Ploussard G; Cathelineau X; Desgrandchamps F; Mongiat-Artus P; Feugeas JP
    Am J Surg Pathol; 2018 Apr; 42(4):423-441. PubMed ID: 29356723
    [TBL] [Abstract][Full Text] [Related]  

  • 12. CT-based transformer model for non-invasively predicting the Fuhrman nuclear grade of clear cell renal cell carcinoma.
    Yang M; He X; Xu L; Liu M; Deng J; Cheng X; Wei Y; Li Q; Wan S; Zhang F; Wu L; Wang X; Song B; Liu M
    Front Oncol; 2022; 12():961779. PubMed ID: 36249050
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Integrative radiogenomics analysis for predicting molecular features and survival in clear cell renal cell carcinoma.
    Zeng H; Chen L; Wang M; Luo Y; Huang Y; Ma X
    Aging (Albany NY); 2021 Mar; 13(7):9960-9975. PubMed ID: 33795526
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Preoperative prediction of pathological grading of hepatocellular carcinoma using machine learning-based ultrasomics: A multicenter study.
    Ren S; Qi Q; Liu S; Duan S; Mao B; Chang Z; Zhang Y; Wang S; Zhang L
    Eur J Radiol; 2021 Oct; 143():109891. PubMed ID: 34481117
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Evaluation of increased preoperative serum high sensitive C-reactive protein and procalcitonin levels on grade and stage of clear cell renal cell carcinoma.
    Hamidi N; Gökçe MI; Süer E; Baltaci S
    Clin Nephrol; 2015 Apr; 83(4):225-30. PubMed ID: 25707457
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Preoperative Prediction of Pancreatic Neuroendocrine Neoplasms Grading Based on Enhanced Computed Tomography Imaging: Validation of Deep Learning with a Convolutional Neural Network.
    Luo Y; Chen X; Chen J; Song C; Shen J; Xiao H; Chen M; Li ZP; Huang B; Feng ST
    Neuroendocrinology; 2020; 110(5):338-350. PubMed ID: 31525737
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Deep learning with a convolutional neural network model to differentiate renal parenchymal tumors: a preliminary study.
    Zheng Y; Wang S; Chen Y; Du HQ
    Abdom Radiol (NY); 2021 Jul; 46(7):3260-3268. PubMed ID: 33656574
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Enhanced computed tomography radiomics-based machine-learning methods for predicting the Fuhrman grades of renal clear cell carcinoma.
    Yin RH; Yang YC; Tang XQ; Shi HF; Duan SF; Pan CJ
    J Xray Sci Technol; 2021; 29(6):1149-1160. PubMed ID: 34657848
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.