These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
3. A Reliable Multi-classifier Multi-objective Model for Predicting Recurrence in Triple Negative Breast Cancer Chen X; Zhou Z; Thomas K; Folkert M; Kim N; Rahimi A; Wang J Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():2182-2185. PubMed ID: 31946334 [TBL] [Abstract][Full Text] [Related]
4. 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]
5. Machine learning-based unenhanced CT texture analysis for predicting BAP1 mutation status of clear cell renal cell carcinomas. Kocak B; Durmaz ES; Kaya OK; Kilickesmez O Acta Radiol; 2020 Jun; 61(6):856-864. PubMed ID: 31635476 [TBL] [Abstract][Full Text] [Related]
7. Radiogenomic analysis based on lipid metabolism-related subset for non-invasive prediction for prognosis of renal clear cell carcinoma. He H; Xie Y; Song F; Feng Z; Rong P Eur J Radiol; 2024 Jun; 175():111433. PubMed ID: 38554673 [TBL] [Abstract][Full Text] [Related]
9. Deep feature classification of angiomyolipoma without visible fat and renal cell carcinoma in abdominal contrast-enhanced CT images with texture image patches and hand-crafted feature concatenation. Lee H; Hong H; Kim J; Jung DC Med Phys; 2018 Apr; 45(4):1550-1561. PubMed ID: 29474742 [TBL] [Abstract][Full Text] [Related]
10. 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; 44(7):3604-3614. PubMed ID: 28376281 [TBL] [Abstract][Full Text] [Related]
11. CT-based machine learning model to predict the Fuhrman nuclear grade of clear cell renal cell carcinoma. Lin F; Cui EM; Lei Y; Luo LP Abdom Radiol (NY); 2019 Jul; 44(7):2528-2534. PubMed ID: 30919041 [TBL] [Abstract][Full Text] [Related]
12. Semantic Computed Tomography Features for Predicting BRCA1-associated Protein 1 and/or Tumor Protein p53 Gene Mutation Status in Clear Cell Renal Cell Carcinoma. Wu XH; Zhu JM; Lin BH; Qiu QR; Ruan ZT; Wei Y; Xue XY; Zheng QS; Chen SH; Xu N Int J Radiat Oncol Biol Phys; 2023 Jul; 116(3):666-675. PubMed ID: 36586494 [TBL] [Abstract][Full Text] [Related]
13. A multi-objective radiomics model for the prediction of locoregional recurrence in head and neck squamous cell cancer. Wang K; Zhou Z; Wang R; Chen L; Zhang Q; Sher D; Wang J Med Phys; 2020 Oct; 47(10):5392-5400. PubMed ID: 32657426 [TBL] [Abstract][Full Text] [Related]
14. CT-based radiomic model predicts high grade of clear cell renal cell carcinoma. Ding J; Xing Z; Jiang Z; Chen J; Pan L; Qiu J; Xing W Eur J Radiol; 2018 Jun; 103():51-56. PubMed ID: 29803385 [TBL] [Abstract][Full Text] [Related]
15. Prognostic Value of a Long Non-coding RNA Signature in Localized Clear Cell Renal Cell Carcinoma. Qu L; Wang ZL; Chen Q; Li YM; He HW; Hsieh JJ; Xue S; Wu ZJ; Liu B; Tang H; Xu XF; Xu F; Wang J; Bao Y; Wang AB; Wang D; Yi XM; Zhou ZK; Shi CJ; Zhong K; Sheng ZC; Zhou YL; Jiang J; Chu XY; He J; Ge JP; Zhang ZY; Zhou WQ; Chen C; Yang JH; Sun YH; Wang LH Eur Urol; 2018 Dec; 74(6):756-763. PubMed ID: 30143382 [TBL] [Abstract][Full Text] [Related]