157 related articles for article (PubMed ID: 37552308)
1. Differentiating thymic epithelial tumors from mediastinal lymphomas: preoperative nomograms based on PET/CT radiomic features to minimize unnecessary anterior mediastinal surgery.
Li J; Cui N; Jiang Z; Li W; Liu W; Wang S; Wang K
J Cancer Res Clin Oncol; 2023 Nov; 149(15):14101-14112. PubMed ID: 37552308
[TBL] [Abstract][Full Text] [Related]
2. The combination of maximum standardized uptake value and clinical parameters for improving the accuracy in distinguishing primary mediastinal lymphomas from thymic epithelial tumors.
Yan H; Wang L; Lei B; Ruan M; Chang C; Zhou M; Liu L; Xie W; Wang Y
Quant Imaging Med Surg; 2024 Feb; 14(2):1944-1956. PubMed ID: 38415117
[TBL] [Abstract][Full Text] [Related]
3. A diagnostic model based on
Zhou S; Tsui P; Lin M; Chen G; Chen W; Cai X
BMC Med Imaging; 2024 Jan; 24(1):14. PubMed ID: 38191331
[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. Computed tomography radiomic feature analysis of thymic epithelial tumors: Differentiation of thymic epithelial tumors from thymic cysts and prediction of histological subtypes.
Zhao W; Ozawa Y; Hara M; Okuda K; Hiwatashi A
Jpn J Radiol; 2024 Apr; 42(4):367-373. PubMed ID: 38010596
[TBL] [Abstract][Full Text] [Related]
6. Multiparameter diagnostic model based on
Wang G; Du L; Lu X; Liu J; Zhang M; Pan Y; Meng X; Xu X; Guan Z; Yang J
BMC Cancer; 2022 Aug; 22(1):895. PubMed ID: 35974323
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Value of metabolic parameters in distinguishing primary mediastinal lymphomas from thymic epithelial tumors.
Zhu L; Li X; Wang J; Fu Q; Liu J; Ma W; Xu W; Chen W
Cancer Biol Med; 2020 May; 17(2):468-477. PubMed ID: 32587782
[No Abstract] [Full Text] [Related]
9. Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan.
Chang CC; Tang EK; Wei YF; Lin CY; Wu FZ; Wu MT; Liu YS; Yen YT; Ma MC; Tseng YL
Front Oncol; 2023; 13():1105100. PubMed ID: 37143945
[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. Deep learning-based radiomic nomogram to predict risk categorization of thymic epithelial tumors: A multicenter study.
Zhou H; Bai HX; Jiao Z; Cui B; Wu J; Zheng H; Yang H; Liao W
Eur J Radiol; 2023 Nov; 168():111136. PubMed ID: 37832194
[TBL] [Abstract][Full Text] [Related]
12. Conventional and radiomic features to predict pathology in the preoperative assessment of anterior mediastinal masses.
Mayoral M; Pagano AM; Araujo-Filho JAB; Zheng J; Perez-Johnston R; Tan KS; Gibbs P; Fernandes Shepherd A; Rimner A; Simone II CB; Riely G; Huang J; Ginsberg MS
Lung Cancer; 2023 Apr; 178():206-212. PubMed ID: 36871345
[TBL] [Abstract][Full Text] [Related]
13. Risk stratification of thymic epithelial tumors by using a nomogram combined with radiomic features and TNM staging.
Shen Q; Shan Y; Xu W; Hu G; Chen W; Feng Z; Pang P; Ding Z; Cai W
Eur Radiol; 2021 Jan; 31(1):423-435. PubMed ID: 32757051
[TBL] [Abstract][Full Text] [Related]
14. Machine-learning-based computed tomography radiomic analysis for histologic subtype classification of thymic epithelial tumours.
Hu J; Zhao Y; Li M; Liu Y; Wang F; Weng Q; You R; Cao D
Eur J Radiol; 2020 May; 126():108929. PubMed ID: 32169748
[TBL] [Abstract][Full Text] [Related]
15. A novel predictive model for distinguishing mediastinal lymphomas from thymic epithelial tumours.
Wang S; Lin M; Yang X; Lin Z; Wang S; Jiang J; Chen G; Ao Y; Gao J; Shi H; Cheng L; Ding J
Eur J Cardiothorac Surg; 2022 Nov; 62(6):. PubMed ID: 36165700
[TBL] [Abstract][Full Text] [Related]
16. Computed Tomography-Based Radiomics for Differentiation of Thymic Epithelial Tumors and Lymphomas in Anterior Mediastinum.
He W; Xia C; Chen X; Yu J; Liu J; Pu H; Li X; Liu S; Chen X; Peng L
Front Oncol; 2022; 12():869982. PubMed ID: 35646676
[TBL] [Abstract][Full Text] [Related]
17. CT-Based Radiomics Signatures for Predicting the Risk Categorization of Thymic Epithelial Tumors.
Liu J; Yin P; Wang S; Liu T; Sun C; Hong N
Front Oncol; 2021; 11():628534. PubMed ID: 33718203
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. 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]
20.
Hu S; Kang Y; Xie Y; Yang T; Yang Y; Jiao J; Zou Q; Zhang H; Zhang Y
Abdom Radiol (NY); 2023 Feb; 48(2):532-542. PubMed ID: 36370179
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]