225 related articles for article (PubMed ID: 34192686)
1. Establishing a survival prediction model for esophageal squamous cell carcinoma based on CT and histopathological images.
Wang J; Wu LL; Zhang Y; Ma G; Lu Y
Phys Med Biol; 2021 Jul; 66(14):. PubMed ID: 34192686
[TBL] [Abstract][Full Text] [Related]
2. Machine learning models predict overall survival and progression free survival of non-surgical esophageal cancer patients with chemoradiotherapy based on CT image radiomics signatures.
Cui Y; Li Z; Xiang M; Han D; Yin Y; Ma C
Radiat Oncol; 2022 Dec; 17(1):212. PubMed ID: 36575480
[TBL] [Abstract][Full Text] [Related]
3. Contrast-enhanced CT-based radiomic analysis for determining the response to anti-programmed death-1 therapy in esophageal squamous cell carcinoma patients: A pilot study.
Yang Q; Huang H; Zhang G; Weng N; Ou Z; Sun M; Luo H; Zhou X; Gao Y; Wu X
Thorac Cancer; 2023 Nov; 14(33):3266-3274. PubMed ID: 37743537
[TBL] [Abstract][Full Text] [Related]
4. A machine learning approach using
Qi WX; Li S; Xiao J; Li H; Chen J; Zhao S
Front Immunol; 2024; 15():1351750. PubMed ID: 38352868
[TBL] [Abstract][Full Text] [Related]
5. Prognostic Modeling of Patients Undergoing Surgery Alone for Esophageal Squamous Cell Carcinoma: A Histopathological and Computed Tomography Based Quantitative Analysis.
Wu LL; Wang JL; Huang W; Liu X; Huang YY; Zeng J; Cui CY; Lu JB; Lin P; Long H; Zhang LJ; Wei J; Lu Y; Ma GW
Front Oncol; 2021; 11():565755. PubMed ID: 33912439
[TBL] [Abstract][Full Text] [Related]
6. A novel CT-based radiomics model for predicting response and prognosis of chemoradiotherapy in esophageal squamous cell carcinoma.
Kasai A; Miyoshi J; Sato Y; Okamoto K; Miyamoto H; Kawanaka T; Tonoiso C; Harada M; Goto M; Yoshida T; Haga A; Takayama T
Sci Rep; 2024 Jan; 14(1):2039. PubMed ID: 38263395
[TBL] [Abstract][Full Text] [Related]
7. The role of spleen radiomics model for predicting prognosis in esophageal squamous cell carcinoma patients receiving definitive radiotherapy.
Guo L; Liu A; Geng X; Zhao Z; Nie Y; Wang L; Liu D; Li Y; Li Y; Li D; Wang Q; Li Z; Liu X; Li M
Thorac Cancer; 2024 Apr; 15(12):947-964. PubMed ID: 38480505
[TBL] [Abstract][Full Text] [Related]
8. A CT-Based Radiomics Nomogram Model for Differentiating Primary Malignant Melanoma of the Esophagus from Esophageal Squamous Cell Carcinoma.
Shi YJ; Zhu HT; Yan S; Li XT; Zhang XY; Sun YS
Biomed Res Int; 2023; 2023():6057196. PubMed ID: 36860814
[TBL] [Abstract][Full Text] [Related]
9. CT radiomics features of meso-esophageal fat in predicting overall survival of patients with locally advanced esophageal squamous cell carcinoma treated by definitive chemoradiotherapy.
Yan S; Li FP; Jian L; Zhu HT; Zhao B; Li XT; Shi YJ; Sun YS
BMC Cancer; 2023 May; 23(1):477. PubMed ID: 37231388
[TBL] [Abstract][Full Text] [Related]
10. Preoperative CT radiomics of esophageal squamous cell carcinoma and lymph node to predict nodal disease with a high diagnostic capability.
Wu YP; Wu L; Ou J; Cao JM; Fu MY; Chen TW; Ouchi E; Hu J
Eur J Radiol; 2024 Jan; 170():111197. PubMed ID: 37992611
[TBL] [Abstract][Full Text] [Related]
11. Computed Tomography-Based Radiomics Nomogram for Predicting the Postoperative Prognosis of Esophageal Squamous Cell Carcinoma: A Multicenter Study.
Peng H; Xue T; Chen Q; Li M; Ge Y; Feng F
Acad Radiol; 2022 Nov; 29(11):1631-1640. PubMed ID: 35300908
[TBL] [Abstract][Full Text] [Related]
12. Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers.
Zhu Y; Yao W; Xu BC; Lei YY; Guo QK; Liu LZ; Li HJ; Xu M; Yan J; Chang DD; Feng ST; Zhu ZH
BMC Cancer; 2021 Oct; 21(1):1167. PubMed ID: 34717582
[TBL] [Abstract][Full Text] [Related]
13. Computed tomography-based deep-learning prediction of neoadjuvant chemoradiotherapy treatment response in esophageal squamous cell carcinoma.
Hu Y; Xie C; Yang H; Ho JWK; Wen J; Han L; Lam KO; Wong IYH; Law SYK; Chiu KWH; Vardhanabhuti V; Fu J
Radiother Oncol; 2021 Jan; 154():6-13. PubMed ID: 32941954
[TBL] [Abstract][Full Text] [Related]
14. Predicting response to CCRT for esophageal squamous carcinoma by a radiomics-clinical SHAP model.
Cheng X; Zhang Y; Zhu M; Sun R; Liu L; Li X
BMC Med Imaging; 2023 Oct; 23(1):145. PubMed ID: 37779188
[TBL] [Abstract][Full Text] [Related]
15. Contrast-enhanced CT radiomics features to preoperatively identify differences between tumor and proximal tumor-adjacent and tumor-distant tissues of resectable esophageal squamous cell carcinoma.
Gao D; Tan BG; Chen XQ; Zhou C; Ou J; Guo WW; Zhou HY; Li R; Zhang XM; Chen TW
Cancer Imaging; 2024 Jan; 24(1):11. PubMed ID: 38243339
[TBL] [Abstract][Full Text] [Related]
16. Prediction of Individual Lymph Node Metastatic Status in Esophageal Squamous Cell Carcinoma Using Routine Computed Tomography Imaging: Comparison of Size-Based Measurements and Radiomics-Based Models.
Xie C; Hu Y; Han L; Fu J; Vardhanabhuti V; Yang H
Ann Surg Oncol; 2022 Dec; 29(13):8117-8126. PubMed ID: 36018524
[TBL] [Abstract][Full Text] [Related]
17. Computed tomography radiomics identification of T1-2 and T3-4 stages of esophageal squamous cell carcinoma: two-dimensional or three-dimensional?
Li Y; Yang L; Gu X; Wang Q; Shi G; Zhang A; Yue M; Wang M; Ren J
Abdom Radiol (NY); 2024 Jan; 49(1):288-300. PubMed ID: 37843576
[TBL] [Abstract][Full Text] [Related]
18. Computed tomography-based radiomics analysis to predict lymphovascular invasion in esophageal squamous cell carcinoma.
Peng H; Yang Q; Xue T; Chen Q; Li M; Duan S; Cai B; Feng F
Br J Radiol; 2022 Feb; 95(1130):20210918. PubMed ID: 34908477
[TBL] [Abstract][Full Text] [Related]
19. A prediction model for degree of differentiation for resectable locally advanced esophageal squamous cell carcinoma based on CT images using radiomics and machine-learning.
Kawahara D; Murakami Y; Tani S; Nagata Y
Br J Radiol; 2021 Aug; 94(1124):20210525. PubMed ID: 34235955
[TBL] [Abstract][Full Text] [Related]
20. Decoding tumor stage by peritumoral and intratumoral radiomics in resectable esophageal squamous cell carcinoma.
Tan XZ; Ma R; Liu P; Xiao CH; Zhang HH; Yang F; Liang CH; Liu ZY
Abdom Radiol (NY); 2024 Jan; 49(1):301-311. PubMed ID: 37831168
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]