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 *

274 related articles for article (PubMed ID: 36219519)

  • 1. Attention-based Deep Learning for the Preoperative Differentiation of Axillary Lymph Node Metastasis in Breast Cancer on DCE-MRI.
    Gao J; Zhong X; Li W; Li Q; Shao H; Wang Z; Dai Y; Ma H; Shi Y; Zhang H; Duan S; Zhang K; Yang P; Zhao F; Zhang H; Xie H; Mao N
    J Magn Reson Imaging; 2023 Jun; 57(6):1842-1853. PubMed ID: 36219519
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Multitask Deep Learning-Based Whole-Process System for Automatic Diagnosis of Breast Lesions and Axillary Lymph Node Metastasis Discrimination from Dynamic Contrast-Enhanced-MRI: A Multicenter Study.
    Zhou H; Hua Z; Gao J; Lin F; Chen Y; Zhang S; Zheng T; Wang Z; Shao H; Li W; Liu F; Li Q; Chen J; Wang X; Zhao F; Qu N; Xie H; Ma H; Zhang H; Mao N
    J Magn Reson Imaging; 2024 May; 59(5):1710-1722. PubMed ID: 37497811
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. 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]  

  • 5. Comparison of Traditional Radiomics, Deep Learning Radiomics and Fusion Methods for Axillary Lymph Node Metastasis Prediction in Breast Cancer.
    Li X; Yang L; Jiao X
    Acad Radiol; 2023 Jul; 30(7):1281-1287. PubMed ID: 36376154
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Non-invasive prediction model of axillary lymph node status in patients with early-stage breast cancer: a feasibility study based on dynamic contrast-enhanced-MRI radiomics.
    Chen W; Lin G; Kong C; Wu X; Hu Y; Chen M; Xia S; Lu C; Xu M; Ji J
    Br J Radiol; 2024 Feb; 97(1154):439-450. PubMed ID: 38308028
    [TBL] [Abstract][Full Text] [Related]  

  • 7. MRI-Based Kinetic Heterogeneity Evaluation in the Accurate Access of Axillary Lymph Node Status in Breast Cancer Using a Hybrid CNN-RNN Model.
    Guo YJ; Yin R; Zhang Q; Han JQ; Dou ZX; Wang PB; Lu H; Liu PF; Chen JJ; Ma WJ
    J Magn Reson Imaging; 2024 Jan; ():. PubMed ID: 38205712
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Differentiating axillary lymph node metastasis in invasive breast cancer patients: A comparison of radiomic signatures from multiparametric breast MR sequences.
    Chai R; Ma H; Xu M; Arefan D; Cui X; Liu Y; Zhang L; Wu S; Xu K
    J Magn Reson Imaging; 2019 Oct; 50(4):1125-1132. PubMed ID: 30848041
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Multi-modality radiomics model predicts axillary lymph node metastasis of breast cancer using MRI and mammography.
    Wang Q; Lin Y; Ding C; Guan W; Zhang X; Jia J; Zhou W; Liu Z; Bai G
    Eur Radiol; 2024 Feb; ():. PubMed ID: 38337068
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Lymph node metastasis prediction and biological pathway associations underlying DCE-MRI deep learning radiomics in invasive breast cancer.
    Liu W; Chen W; Xia J; Lu Z; Fu Y; Li Y; Tan Z
    BMC Med Imaging; 2024 Apr; 24(1):91. PubMed ID: 38627678
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction of Axillary Lymph Node Metastasis in Breast Cancer using Intra-peritumoral Textural Transition Analysis based on Dynamic Contrast-enhanced Magnetic Resonance Imaging.
    Zhan C; Hu Y; Wang X; Liu H; Xia L; Ai T
    Acad Radiol; 2022 Jan; 29 Suppl 1():S107-S115. PubMed ID: 33712393
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Difference of DCE-MRI Parameters at Different Time Points and Their Predictive Value for Axillary Lymph Node Metastasis of Breast Cancer.
    Ya G; Wen F; Xing-Ru L; Zhuan-Zhuan G; Jun-Qiang L
    Acad Radiol; 2022 Jan; 29 Suppl 1():S79-S86. PubMed ID: 33504446
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A two-center study of a combined nomogram based on mammography and MRI to predict ALN metastasis in breast cancer.
    Hua Y; Peng Q; Han J; Fei J; Sun A
    Magn Reson Imaging; 2024 Jul; 110():128-137. PubMed ID: 38631535
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Radiomics nomogram for predicting axillary lymph node metastasis in breast cancer based on DCE-MRI: A multicenter study.
    Zhang J; Zhang Z; Mao N; Zhang H; Gao J; Wang B; Ren J; Liu X; Zhang B; Dou T; Li W; Wang Y; Jia H
    J Xray Sci Technol; 2023; 31(2):247-263. PubMed ID: 36744360
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Deep Learning Radiomics of Preoperative Breast MRI for Prediction of Axillary Lymph Node Metastasis in Breast Cancer.
    Chen Y; Wang L; Dong X; Luo R; Ge Y; Liu H; Zhang Y; Wang D
    J Digit Imaging; 2023 Aug; 36(4):1323-1331. PubMed ID: 36973631
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. A delta-radiomic lymph node model using dynamic contrast enhanced MRI for the early prediction of axillary response after neoadjuvant chemotherapy in breast cancer patients.
    Liu S; Du S; Gao S; Teng Y; Jin F; Zhang L
    BMC Cancer; 2023 Jan; 23(1):15. PubMed ID: 36604679
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer Based on Intratumoral and Peritumoral DCE-MRI Radiomics Nomogram.
    Liu Y; Li X; Zhu L; Zhao Z; Wang T; Zhang X; Cai B; Li L; Ma M; Ma X; Ming J
    Contrast Media Mol Imaging; 2022; 2022():6729473. PubMed ID: 36051932
    [TBL] [Abstract][Full Text] [Related]  

  • 20. MRI-Based Breast Cancer Classification and Localization by Multiparametric Feature Extraction and Combination Using Deep Learning.
    Cong C; Li X; Zhang C; Zhang J; Sun K; Liu L; Ambale-Venkatesh B; Chen X; Wang Y
    J Magn Reson Imaging; 2024 Jan; 59(1):148-161. PubMed ID: 37013422
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.