BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

126 related articles for article (PubMed ID: 38663124)

  • 1. CT radiomics based on the peritumoral adipose region of gastric adenocarcinoma for preoperative prediction of lymph node metastasis.
    Ding XM; Zhou HY; Wang YS; Cao JM; Ou J; Zhang XM; Chen TW
    Eur J Radiol; 2024 Jun; 175():111479. PubMed ID: 38663124
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A radiomics-based model for prediction of lymph node metastasis in gastric cancer.
    Gao X; Ma T; Cui J; Zhang Y; Wang L; Li H; Ye Z
    Eur J Radiol; 2020 Aug; 129():109069. PubMed ID: 32464581
    [TBL] [Abstract][Full Text] [Related]  

  • 3. [The value of spectral CT-based radiomics in preoperative prediction of lymph node metastasis of advanced gastric cancer].
    Wang R; Li J; Fang MJ; Dong D; Liang P; Gao JB
    Zhonghua Yi Xue Za Zhi; 2020 Jun; 100(21):1617-1622. PubMed ID: 32486595
    [No Abstract]   [Full Text] [Related]  

  • 4. Radiomics signature based on computed tomography images for the preoperative prediction of lymph node metastasis at individual stations in gastric cancer: A multicenter study.
    Sun Z; Jiang Y; Chen C; Zheng H; Huang W; Xu B; Tang W; Yuan Q; Zhou K; Liang X; Chen H; Han Z; Feng H; Yu S; Hu Y; Yu J; Zhou Z; Wang W; Xu Y; Li G
    Radiother Oncol; 2021 Dec; 165():179-190. PubMed ID: 34774652
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Incremental value of PET primary lesion-based radiomics signature to conventional metabolic parameters and traditional risk factors for preoperative prediction of lymph node metastases in gastric cancer.
    Xue XQ; Yu WJ; Shao XL; Wang YT
    Abdom Radiol (NY); 2023 Feb; 48(2):510-518. PubMed ID: 36418614
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. A CT-based Radiomics Model for Prediction of Lymph Node Metastasis in Early Stage Gastric Cancer.
    Gao X; Ma T; Cui J; Zhang Y; Wang L; Li H; Ye Z
    Acad Radiol; 2021 Jun; 28(6):e155-e164. PubMed ID: 32507613
    [TBL] [Abstract][Full Text] [Related]  

  • 8. CT radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer.
    Wang Y; Liu W; Yu Y; Liu JJ; Xue HD; Qi YF; Lei J; Yu JC; Jin ZY
    Eur Radiol; 2020 Feb; 30(2):976-986. PubMed ID: 31468157
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Preoperative prediction of lymph node metastasis in colorectal cancer using
    Wang Y; Zhao H; Fu P; Tian L; Su Y; Lyu Z; Gu W; Wang Y; Liu S; Wang X; Zheng H; Du J; Zhang R
    Med Phys; 2024 May; ():. PubMed ID: 38801340
    [TBL] [Abstract][Full Text] [Related]  

  • 10.
    Xue XQ; Yu WJ; Shi X; Shao XL; Wang YT
    Front Oncol; 2022; 12():911168. PubMed ID: 36003788
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Comparison of MRI and CT-based radiomics for preoperative prediction of lymph node metastasis in pancreatic ductal adenocarcinoma.
    Zeng P; Qu C; Liu J; Cui J; Liu X; Xiu D; Yuan H
    Acta Radiol; 2023 Jul; 64(7):2221-2228. PubMed ID: 36474439
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Radiomics for differentiating tumor deposits from lymph node metastasis in rectal cancer.
    Zhang YC; Li M; Jin YM; Xu JX; Huang CC; Song B
    World J Gastroenterol; 2022 Aug; 28(29):3960-3970. PubMed ID: 36157536
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Can peritumoral radiomics increase the efficiency of the prediction for lymph node metastasis in clinical stage T1 lung adenocarcinoma on CT?
    Wang X; Zhao X; Li Q; Xia W; Peng Z; Zhang R; Li Q; Jian J; Wang W; Tang Y; Liu S; Gao X
    Eur Radiol; 2019 Nov; 29(11):6049-6058. PubMed ID: 30887209
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A deep learning-based radiomics model for predicting lymph node status from lung adenocarcinoma.
    Xie H; Song C; Jian L; Guo Y; Li M; Luo J; Li Q; Tan T
    BMC Med Imaging; 2024 May; 24(1):121. PubMed ID: 38789936
    [TBL] [Abstract][Full Text] [Related]  

  • 15. [A nomogram for predicting lymph node metastasis in early gastric cancer].
    Cui H; Cao B; Deng H; Liu GB; Liang WQ; Xie TY; Ye L; Zhang QP; Wang N; Liu FD; Wei B
    Zhonghua Wei Chang Wai Ke Za Zhi; 2022 Jan; 25(1):40-47. PubMed ID: 35067033
    [No Abstract]   [Full Text] [Related]  

  • 16. Development and evaluation of a venous computed tomography radiomics model to predict lymph node metastasis from non-small cell lung cancer.
    Cong M; Yao H; Liu H; Huang L; Shi G
    Medicine (Baltimore); 2020 May; 99(18):e20074. PubMed ID: 32358390
    [TBL] [Abstract][Full Text] [Related]  

  • 17. MRI-based multiregional radiomics for preoperative prediction of tumor deposit and prognosis in resectable rectal cancer: a bicenter study.
    Li H; Chen XL; Liu H; Liu YS; Li ZL; Pang MH; Pu H
    Eur Radiol; 2023 Nov; 33(11):7561-7572. PubMed ID: 37160427
    [TBL] [Abstract][Full Text] [Related]  

  • 18. The significance of preoperative serum carcinoembryonic antigen levels in the prediction of lymph node metastasis and prognosis in locally advanced gastric cancer: a retrospective analysis.
    Wang K; Jiang X; Ren Y; Ma Z; Cheng X; Li F; Xiao J; Yu Z; Jiao Z
    BMC Gastroenterol; 2020 Apr; 20(1):100. PubMed ID: 32276616
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Integrating No.3 lymph nodes and primary tumor radiomics to predict lymph node metastasis in T1-2 gastric cancer.
    Wang X; Li C; Fang M; Zhang L; Zhong L; Dong D; Tian J; Shan X
    BMC Med Imaging; 2021 Mar; 21(1):58. PubMed ID: 33757460
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Noninvasive prediction of lymph node status for patients with early-stage cervical cancer based on radiomics features from ultrasound images.
    Jin X; Ai Y; Zhang J; Zhu H; Jin J; Teng Y; Chen B; Xie C
    Eur Radiol; 2020 Jul; 30(7):4117-4124. PubMed ID: 32078013
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.