These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

369 related articles for article (PubMed ID: 35734595)

  • 1. MRI-Based Radiomics for Preoperative Prediction of Lymphovascular Invasion in Patients With Invasive Breast Cancer.
    Nijiati M; Aihaiti D; Huojia A; Abulizi A; Mutailifu S; Rouzi N; Dai G; Maimaiti P
    Front Oncol; 2022; 12():876624. PubMed ID: 35734595
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based radiomics.
    Liu Z; Feng B; Li C; Chen Y; Chen Q; Li X; Guan J; Chen X; Cui E; Li R; Li Z; Long W
    J Magn Reson Imaging; 2019 Sep; 50(3):847-857. PubMed ID: 30773770
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Intra- and Peritumoral Based Radiomics for Assessment of Lymphovascular Invasion in Invasive Breast Cancer.
    Jiang W; Meng R; Cheng Y; Wang H; Han T; Qu N; Yu T; Hou Y; Xu S
    J Magn Reson Imaging; 2024 Feb; 59(2):613-625. PubMed ID: 37199241
    [TBL] [Abstract][Full Text] [Related]  

  • 4. [Preoperative prediction of HER-2 expression status in breast cancer based on MRI radiomics model].
    Zhang Y; Huang H; Yin L; Wang ZX; Lu SY; Wang XX; Xiang LL; Zhang Q; Zhang JL; Shan XH
    Zhonghua Zhong Liu Za Zhi; 2024 May; 46(5):428-437. PubMed ID: 38742356
    [No Abstract]   [Full Text] [Related]  

  • 5. Multiparametric MRI-based radiomics nomogram for preoperative prediction of lymphovascular invasion and clinical outcomes in patients with breast invasive ductal carcinoma.
    Zhang J; Wang G; Ren J; Yang Z; Li D; Cui Y; Yang X
    Eur Radiol; 2022 Jun; 32(6):4079-4089. PubMed ID: 35050415
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Predictive value of MRI-based deep learning model for lymphovascular invasion status in node-negative invasive breast cancer.
    Liang R; Li F; Yao J; Tong F; Hua M; Liu J; Shi C; Sui L; Lu H
    Sci Rep; 2024 Jul; 14(1):16204. PubMed ID: 39003325
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Assessment of Lymphovascular Invasion in Breast Cancer Using a Combined MRI Morphological Features, Radiomics, and Deep Learning Approach Based on Dynamic Contrast-Enhanced MRI.
    Yang X; Fan X; Lin S; Zhou Y; Liu H; Wang X; Zuo Z; Zeng Y
    J Magn Reson Imaging; 2024 Jun; 59(6):2238-2249. PubMed ID: 37855421
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A clinical-radiomics model incorporating T2-weighted and diffusion-weighted magnetic resonance images predicts the existence of lymphovascular invasion / perineural invasion in patients with colorectal cancer.
    Zhang K; Ren Y; Xu S; Lu W; Xie S; Qu J; Wang X; Shen B; Pang P; Cai X; Sun J
    Med Phys; 2021 Sep; 48(9):4872-4882. PubMed ID: 34042185
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Leveraging multimodal MRI-based radiomics analysis with diverse machine learning models to evaluate lymphovascular invasion in clinically node-negative breast cancer.
    Jiang Y; Zeng Y; Zuo Z; Yang X; Liu H; Zhou Y; Fan X
    Heliyon; 2024 Jan; 10(1):e23916. PubMed ID: 38192872
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Multiphases DCE-MRI Radiomics Nomogram for Preoperative Prediction of Lymphovascular Invasion in Invasive Breast Cancer.
    Ma Q; Lu X; Chen Q; Gong H; Lei J
    Acad Radiol; 2024 Dec; 31(12):4743-4758. PubMed ID: 39107190
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction of lymphovascular invasion in invasive breast cancer based on clinical-MRI radiomics features.
    Zhang C; Zhou P; Li R; Li Z; Ouyang A
    BMC Med Imaging; 2024 Oct; 24(1):277. PubMed ID: 39415127
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Biparametric magnetic resonance imaging-based radiomics features for prediction of lymphovascular invasion in rectal cancer.
    Tong P; Sun D; Chen G; Ni J; Li Y
    BMC Cancer; 2023 Jan; 23(1):61. PubMed ID: 36650498
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multi-Parametric Magnetic Resonance Imaging-Based Radiomics Analysis of Cervical Cancer for Preoperative Prediction of Lymphovascular Space Invasion.
    Huang G; Cui Y; Wang P; Ren J; Wang L; Ma Y; Jia Y; Ma X; Zhao L
    Front Oncol; 2021; 11():663370. PubMed ID: 35096556
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Machine learning model based on enhanced CT radiomics for the preoperative prediction of lymphovascular invasion in esophageal squamous cell carcinoma.
    Wang Y; Bai G; Huang M; Chen W
    Front Oncol; 2024; 14():1308317. PubMed ID: 38549935
    [TBL] [Abstract][Full Text] [Related]  

  • 15. MRI Radiomics of Breast Cancer: Machine Learning-Based Prediction of Lymphovascular Invasion Status.
    Kayadibi Y; Kocak B; Ucar N; Akan YN; Yildirim E; Bektas S
    Acad Radiol; 2022 Jan; 29 Suppl 1():S126-S134. PubMed ID: 34876340
    [TBL] [Abstract][Full Text] [Related]  

  • 16. MRI radiomics for the preoperative evaluation of lymphovascular invasion in breast cancer: A meta-analysis.
    Ma Q; Li Z; Li W; Chen Q; Liu X; Feng W; Lei J
    Eur J Radiol; 2023 Nov; 168():111127. PubMed ID: 37801997
    [TBL] [Abstract][Full Text] [Related]  

  • 17. T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma.
    Zheng HD; Huang QY; Huang QM; Ke XT; Ye K; Lin S; Xu JH
    World J Gastrointest Oncol; 2024 Mar; 16(3):819-832. PubMed ID: 38577440
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study.
    Yu Y; He Z; Ouyang J; Tan Y; Chen Y; Gu Y; Mao L; Ren W; Wang J; Lin L; Wu Z; Liu J; Ou Q; Hu Q; Li A; Chen K; Li C; Lu N; Li X; Su F; Liu Q; Xie C; Yao H
    EBioMedicine; 2021 Jul; 69():103460. PubMed ID: 34233259
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Evaluation of Lymph Node Metastasis in Advanced Gastric Cancer Using Magnetic Resonance Imaging-Based Radiomics.
    Chen W; Wang S; Dong D; Gao X; Zhou K; Li J; Lv B; Li H; Wu X; Fang M; Tian J; Xu M
    Front Oncol; 2019; 9():1265. PubMed ID: 31824847
    [No Abstract]   [Full Text] [Related]  

  • 20. Radiomics Based on T2-Weighted Imaging and Apparent Diffusion Coefficient Images for Preoperative Evaluation of Lymph Node Metastasis in Rectal Cancer Patients.
    Li C; Yin J
    Front Oncol; 2021; 11():671354. PubMed ID: 34041033
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 19.