150 related articles for article (PubMed ID: 37188857)
1. Evaluation the benefits of additional radiotherapy for gastric cancer patients after D2 resection using CT based radiomics.
Zheng H; Zheng Q; Jiang M; Chen D; Han C; Yi J; Ai Y; Yan J; Jin X
Radiol Med; 2023 Jun; 128(6):679-688. PubMed ID: 37188857
[TBL] [Abstract][Full Text] [Related]
2. Contrast-enhanced CT based radiomics in the preoperative prediction of perineural invasion for patients with gastric cancer.
Zheng H; Zheng Q; Jiang M; Han C; Yi J; Ai Y; Xie C; Jin X
Eur J Radiol; 2022 Sep; 154():110393. PubMed ID: 35679700
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Radiomics based on machine learning algorithms could predict prognosis and postoperative chemotherapy benefits of patients with gastric cancer: a retrospective cohort study.
Xiang Y; Hu Y; Chen C; Zhi H; Zhang Z; Lu M; Chen X; Luo Z; Chen S; Dias-Neto E; Pizzini P; Chen X; Chen X; Zhuang Y; Dong Q
J Gastrointest Oncol; 2023 Oct; 14(5):2048-2063. PubMed ID: 37969820
[TBL] [Abstract][Full Text] [Related]
5. Prognostic aspects of lymphovascular invasion in localized gastric cancer: new insights into the radiomics and deep transfer learning from contrast-enhanced CT imaging.
Li Q; Feng QX; Qi L; Liu C; Zhang J; Yang G; Zhang YD; Liu XS
Abdom Radiol (NY); 2022 Feb; 47(2):496-507. PubMed ID: 34766197
[TBL] [Abstract][Full Text] [Related]
6. Radiomics signature of computed tomography imaging for prediction of survival and chemotherapeutic benefits in gastric cancer.
Jiang Y; Chen C; Xie J; Wang W; Zha X; Lv W; Chen H; Hu Y; Li T; Yu J; Zhou Z; Xu Y; Li G
EBioMedicine; 2018 Oct; 36():171-182. PubMed ID: 30224313
[TBL] [Abstract][Full Text] [Related]
7. Evaluation of dual-energy CT derived radiomics signatures in predicting outcomes in patients with advanced gastric cancer after neoadjuvant chemotherapy.
Chen Y; Yuan F; Wang L; Li E; Xu Z; Wels M; Yao W; Zhang H
Eur J Surg Oncol; 2022 Feb; 48(2):339-347. PubMed ID: 34304951
[TBL] [Abstract][Full Text] [Related]
8. [Establishment and validation of a predictive nomogram model for advanced gastric cancer with perineural invasion].
Liu SH; Hou XY; Zhang XX; Liu GW; Xin FJ; Wang JG; Zhang DL; Wang DS; Lu Y
Zhonghua Wei Chang Wai Ke Za Zhi; 2020 Nov; 23(11):1059-1066. PubMed ID: 33212554
[No Abstract] [Full Text] [Related]
9. Association of Tumor-Associated Collagen Signature With Prognosis and Adjuvant Chemotherapy Benefits in Patients With Gastric Cancer.
Chen D; Chen H; Chi L; Fu M; Wang G; Wu Z; Xu S; Sun C; Xu X; Lin L; Cheng J; Jiang W; Dong X; Lu J; Zheng J; Chen G; Li G; Zhuo S; Yan J
JAMA Netw Open; 2021 Nov; 4(11):e2136388. PubMed ID: 34846524
[TBL] [Abstract][Full Text] [Related]
10. A radiomics nomogram analysis based on CT images and clinical features for preoperative Lauren classification in gastric cancer.
Nie T; Liu D; Ai S; He Y; Yang M; Chen J; Yuan Z; Liu Y
Jpn J Radiol; 2023 Apr; 41(4):401-408. PubMed ID: 36370327
[TBL] [Abstract][Full Text] [Related]
11. Radiomics signature for predicting postoperative disease-free survival of patients with gastric cancer: development and validation of a predictive nomogram.
Shi S; Miao Z; Zhou Y; Xu C; Zhang X
Diagn Interv Radiol; 2022 Sep; 28(5):441-449. PubMed ID: 36097638
[TBL] [Abstract][Full Text] [Related]
12. Dual-energy CT-based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer.
Li J; Dong D; Fang M; Wang R; Tian J; Li H; Gao J
Eur Radiol; 2020 Apr; 30(4):2324-2333. PubMed ID: 31953668
[TBL] [Abstract][Full Text] [Related]
13. Prognostic value of computed tomography radiomics features in patients with gastric cancer following curative resection.
Li W; Zhang L; Tian C; Song H; Fang M; Hu C; Zang Y; Cao Y; Dai S; Wang F; Dong D; Wang R; Tian J
Eur Radiol; 2019 Jun; 29(6):3079-3089. PubMed ID: 30519931
[TBL] [Abstract][Full Text] [Related]
14. Radiomics analysis of contrast-enhanced CT predicts lymphovascular invasion and disease outcome in gastric cancer: a preliminary study.
Chen X; Yang Z; Yang J; Liao Y; Pang P; Fan W; Chen X
Cancer Imaging; 2020 Apr; 20(1):24. PubMed ID: 32248822
[TBL] [Abstract][Full Text] [Related]
15. Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer.
Wang XX; Ding Y; Wang SW; Dong D; Li HL; Chen J; Hu H; Lu C; Tian J; Shan XH
Cancer Imaging; 2020 Nov; 20(1):83. PubMed ID: 33228815
[TBL] [Abstract][Full Text] [Related]
16. Outcome prediction in resectable lung adenocarcinoma patients: value of CT radiomics.
Choe J; Lee SM; Do KH; Kim S; Choi S; Lee JG; Seo JB
Eur Radiol; 2020 Sep; 30(9):4952-4963. PubMed ID: 32356158
[TBL] [Abstract][Full Text] [Related]
17. Prediction of response to neoadjuvant chemotherapy in advanced gastric cancer: A radiomics nomogram analysis based on CT images and clinicopathological features.
Tan X; Yang X; Hu S; Ge Y; Wu Q; Wang J; Sun Z
J Xray Sci Technol; 2023; 31(1):49-61. PubMed ID: 36314190
[TBL] [Abstract][Full Text] [Related]
18. Radiomics signature for prediction of long-term survival and recurrence patterns in patients with gastric cancer after radical gastrectomy: A multicenter study.
Huang JM; Zhuang LP; Wang HG; Zhong LY; Xue SJ; Tian FX; Lin HY
Saudi J Gastroenterol; 2023; 29(1):21-30. PubMed ID: 36588364
[TBL] [Abstract][Full Text] [Related]
19. Radiomic signature of
Jiang Y; Yuan Q; Lv W; Xi S; Huang W; Sun Z; Chen H; Zhao L; Liu W; Hu Y; Lu L; Ma J; Li T; Yu J; Wang Q; Li G
Theranostics; 2018; 8(21):5915-5928. PubMed ID: 30613271
[TBL] [Abstract][Full Text] [Related]
20. Deep learning-based radiomics model can predict extranodal soft tissue metastasis in gastric cancer.
Liu S; Deng J; Dong D; Fang M; Ye Z; Hu Y; Li H; Zhong L; Cao R; Zhao X; Shang W; Li G; Liang H; Tian J
Med Phys; 2024 Jan; 51(1):267-277. PubMed ID: 37573524
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]