214 related articles for article (PubMed ID: 37711814)
1. The predictive value of a computed tomography-based radiomics model for the surgical separability of thymic epithelial tumors from the superior vena cava and the left innominate vein.
Li Z; Wang F; Zhang H; Zheng H; Zhou X; Wang Z; Xie S; Peng L; Wang X; Wang Y
Quant Imaging Med Surg; 2023 Sep; 13(9):5622-5640. PubMed ID: 37711814
[TBL] [Abstract][Full Text] [Related]
2. 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; 33(10):6804-6816. PubMed ID: 37148352
[TBL] [Abstract][Full Text] [Related]
3. 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 Mar-Apr 01; 47(2):220-228. PubMed ID: 36877755
[TBL] [Abstract][Full Text] [Related]
4. 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; 166():150-160. PubMed ID: 35287067
[TBL] [Abstract][Full Text] [Related]
5. Application Values of 2D and 3D Radiomics Models Based on CT Plain Scan in Differentiating Benign from Malignant Ovarian Tumors.
Li S; Liu J; Xiong Y; Han Y; Pang P; Luo P; Fan B
Biomed Res Int; 2022; 2022():5952296. PubMed ID: 35224097
[TBL] [Abstract][Full Text] [Related]
6. A radiomics model to predict the invasiveness of thymic epithelial tumors based on contrast‑enhanced computed tomography.
Chen X; Feng B; Li C; Duan X; Chen Y; Li Z; Liu Z; Zhang C; Long W
Oncol Rep; 2020 Apr; 43(4):1256-1266. PubMed ID: 32323834
[TBL] [Abstract][Full Text] [Related]
7. Application of a combined radiomics nomogram based on CE-CT in the preoperative prediction of thymomas risk categorization.
Dong W; Xiong S; Lei P; Wang X; Liu H; Liu Y; Zou H; Fan B; Qiu Y
Front Oncol; 2022; 12():944005. PubMed ID: 36081562
[TBL] [Abstract][Full Text] [Related]
8. Differentiation of Clear Cell and Non-clear-cell Renal Cell Carcinoma through CT-based Radiomics Models and Nomogram.
Cheng D; Abudikeranmu Y; Tuerdi B
Curr Med Imaging; 2023; 19(9):1005-1017. PubMed ID: 36411581
[TBL] [Abstract][Full Text] [Related]
9. CT-Based Radiomics Signature With Machine Learning Predicts MYCN Amplification in Pediatric Abdominal Neuroblastoma.
Chen X; Wang H; Huang K; Liu H; Ding H; Zhang L; Zhang T; Yu W; He L
Front Oncol; 2021; 11():687884. PubMed ID: 34109133
[TBL] [Abstract][Full Text] [Related]
10. CT-Based Radiomics Nomogram for Differentiation of Anterior Mediastinal Thymic Cyst From Thymic Epithelial Tumor.
Zhang C; Yang Q; Lin F; Ma H; Zhang H; Zhang R; Wang P; Mao N
Front Oncol; 2021; 11():744021. PubMed ID: 34956869
[TBL] [Abstract][Full Text] [Related]
11. Extrathyroidal Extension Prediction of Papillary Thyroid Cancer With Computed Tomography Based Radiomics Nomogram: A Multicenter Study.
Yu P; Wu X; Li J; Mao N; Zhang H; Zheng G; Han X; Dong L; Che K; Wang Q; Li G; Mou Y; Song X
Front Endocrinol (Lausanne); 2022; 13():874396. PubMed ID: 35721715
[TBL] [Abstract][Full Text] [Related]
12. A radiomics approach for automated diagnosis of ovarian neoplasm malignancy in computed tomography.
Li S; Liu J; Xiong Y; Pang P; Lei P; Zou H; Zhang M; Fan B; Luo P
Sci Rep; 2021 Apr; 11(1):8730. PubMed ID: 33888749
[TBL] [Abstract][Full Text] [Related]
13. Machine learning models combining computed tomography semantic features and selected clinical variables for accurate prediction of the pathological grade of bladder cancer.
Deng Z; Dong W; Xiong S; Jin D; Zhou H; Zhang L; Xie L; Deng Y; Xu R; Fan B
Front Oncol; 2023; 13():1166245. PubMed ID: 37223680
[TBL] [Abstract][Full Text] [Related]
14. Development and validation of a CT-texture analysis nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes.
Ren C; Li M; Zhang Y; Zhang S
Cancer Imaging; 2020 Dec; 20(1):86. PubMed ID: 33308325
[TBL] [Abstract][Full Text] [Related]
15. Non-Contrasted CT Radiomics for SAH Prognosis Prediction.
Shan D; Wang J; Qi P; Lu J; Wang D
Bioengineering (Basel); 2023 Aug; 10(8):. PubMed ID: 37627852
[TBL] [Abstract][Full Text] [Related]
16. Preoperative prediction for lauren type of gastric cancer: A radiomics nomogram analysis based on CT images and clinical features.
Sun Z; Jin L; Zhang S; Duan S; Xing W; Hu S
J Xray Sci Technol; 2021; 29(4):675-686. PubMed ID: 34024809
[TBL] [Abstract][Full Text] [Related]
17. Integration of ultrasound radiomics features and clinical factors: A nomogram model for identifying the Ki-67 status in patients with breast carcinoma.
Wu J; Fang Q; Yao J; Ge L; Hu L; Wang Z; Jin G
Front Oncol; 2022; 12():979358. PubMed ID: 36276108
[TBL] [Abstract][Full Text] [Related]
18. Applying a nomogram based on preoperative CT to predict early recurrence of laryngeal squamous cell carcinoma after surgery.
Yao Y; Jia C; Zhang H; Mou Y; Wang C; Han X; Yu P; Mao N; Song X
J Xray Sci Technol; 2023; 31(3):435-452. PubMed ID: 36806538
[TBL] [Abstract][Full Text] [Related]
19. The predictive potential of contrast-enhanced computed tomography based radiomics in the preoperative staging of cT4 gastric cancer.
Liu B; Zhang D; Wang H; Wang H; Zhang P; Zhang D; Zhang Q; Zhang J
Quant Imaging Med Surg; 2022 Nov; 12(11):5222-5238. PubMed ID: 36330185
[TBL] [Abstract][Full Text] [Related]
20. Differentiation of acute and chronic vertebral compression fractures using conventional CT based on deep transfer learning features and hand-crafted radiomics features.
Zhang J; Liu J; Liang Z; Xia L; Zhang W; Xing Y; Zhang X; Tang G
BMC Musculoskelet Disord; 2023 Mar; 24(1):165. PubMed ID: 36879285
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
