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 *

154 related articles for article (PubMed ID: 38607282)

  • 1. Machine Learning Prediction of Lymph Node Metastasis in Breast Cancer: Performance of a Multi-institutional MRI-based 4D Convolutional Neural Network.
    Polat DS; Nguyen S; Karbasi P; Hulsey K; Cobanoglu MC; Wang L; Montillo A; Dogan BE
    Radiol Imaging Cancer; 2024 May; 6(3):e230107. PubMed ID: 38607282
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning.
    Zhou LQ; Wu XL; Huang SY; Wu GG; Ye HR; Wei Q; Bao LY; Deng YB; Li XR; Cui XW; Dietrich CF
    Radiology; 2020 Jan; 294(1):19-28. PubMed ID: 31746687
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Development of a Deep Learning Model to Identify Lymph Node Metastasis on Magnetic Resonance Imaging in Patients With Cervical Cancer.
    Wu Q; Wang S; Zhang S; Wang M; Ding Y; Fang J; Wu Q; Qian W; Liu Z; Sun K; Jin Y; Ma H; Tian J
    JAMA Netw Open; 2020 Jul; 3(7):e2011625. PubMed ID: 32706384
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Preoperative prediction of sentinel lymph node metastasis in breast cancer by radiomic signatures from dynamic contrast-enhanced MRI.
    Liu C; Ding J; Spuhler K; Gao Y; Serrano Sosa M; Moriarty M; Hussain S; He X; Liang C; Huang C
    J Magn Reson Imaging; 2019 Jan; 49(1):131-140. PubMed ID: 30171822
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Convolutional Neural Network of Multiparametric MRI Accurately Detects Axillary Lymph Node Metastasis in Breast Cancer Patients With Pre Neoadjuvant Chemotherapy.
    Ren T; Lin S; Huang P; Duong TQ
    Clin Breast Cancer; 2022 Feb; 22(2):170-177. PubMed ID: 34384696
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Convolutional Neural Network Detection of Axillary Lymph Node Metastasis Using Standard Clinical Breast MRI.
    Ren T; Cattell R; Duanmu H; Huang P; Li H; Vanguri R; Liu MZ; Jambawalikar S; Ha R; Wang F; Cohen J; Bernstein C; Bangiyev L; Duong TQ
    Clin Breast Cancer; 2020 Jun; 20(3):e301-e308. PubMed ID: 32139272
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score.
    Ha R; Chang P; Mutasa S; Karcich J; Goodman S; Blum E; Kalinsky K; Liu MZ; Jambawalikar S
    J Magn Reson Imaging; 2019 Feb; 49(2):518-524. PubMed ID: 30129697
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Development and Validation of a Preoperative Magnetic Resonance Imaging Radiomics-Based Signature to Predict Axillary Lymph Node Metastasis and Disease-Free Survival in Patients With Early-Stage Breast Cancer.
    Yu Y; Tan Y; Xie C; Hu Q; Ouyang J; Chen Y; Gu Y; Li A; Lu N; He Z; Yang Y; Chen K; Ma J; Li C; Ma M; Li X; Zhang R; Zhong H; Ou Q; Zhang Y; He Y; Li G; Wu Z; Su F; Song E; Yao H
    JAMA Netw Open; 2020 Dec; 3(12):e2028086. PubMed ID: 33289845
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Development and validation of convolutional neural network-based model to predict the risk of sentinel or non-sentinel lymph node metastasis in patients with breast cancer: a machine learning study.
    Chen M; Kong C; Lin G; Chen W; Guo X; Chen Y; Cheng X; Chen M; Shi C; Xu M; Sun J; Lu C; Ji J
    EClinicalMedicine; 2023 Sep; 63():102176. PubMed ID: 37662514
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Preoperative Prediction of Lymph Node Metastasis from Clinical DCE MRI of the Primary Breast Tumor Using a 4D CNN.
    Nguyen S; Polat D; Karbasi P; Moser D; Wang L; Hulsey K; Çobanoğlu MC; Dogan B; Montillo A
    Med Image Comput Comput Assist Interv; 2020 Oct; 12262():326-334. PubMed ID: 33768221
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A non-invasive preoperative prediction model for predicting axillary lymph node metastasis in breast cancer based on a machine learning approach: combining ultrasonographic parameters and breast gamma specific imaging features.
    Cai R; Deng L; Zhang H; Zhang H; Wu Q
    Radiat Oncol; 2024 May; 19(1):63. PubMed ID: 38802938
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Dynamic contrast-enhanced and diffusion-weighted MRI of invasive breast cancer for the prediction of sentinel lymph node status.
    Choi EJ; Youk JH; Choi H; Song JS
    J Magn Reson Imaging; 2020 Feb; 51(2):615-626. PubMed ID: 31313393
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Predicting of axillary lymph node metastasis in invasive breast cancer using multiparametric MRI dataset based on CNN model.
    Zhang X; Liu M; Ren W; Sun J; Wang K; Xi X; Zhang G
    Front Oncol; 2022; 12():1069733. PubMed ID: 36561533
    [TBL] [Abstract][Full Text] [Related]  

  • 17. [Establishment of artificial neural network model for predicting lymph node metastasis in patients with stage Ⅱ-Ⅲ gastric cancer].
    Xue Z; Lu J; Lin J; Huang CM; Li P; Xie JW; Wang JB; Lin JX; Chen QY; Zheng CH
    Zhonghua Wei Chang Wai Ke Za Zhi; 2022 Apr; 25(4):327-335. PubMed ID: 35461201
    [No Abstract]   [Full Text] [Related]  

  • 18. Multi-input deep learning architecture for predicting breast tumor response to chemotherapy using quantitative MR images.
    El Adoui M; Drisis S; Benjelloun M
    Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1491-1500. PubMed ID: 32556920
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Axillary Lymph Node Evaluation Utilizing Convolutional Neural Networks Using MRI Dataset.
    Ha R; Chang P; Karcich J; Mutasa S; Fardanesh R; Wynn RT; Liu MZ; Jambawalikar S
    J Digit Imaging; 2018 Dec; 31(6):851-856. PubMed ID: 29696472
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 8.