Connection

Co-Authors

This is a "connection" page, showing publications co-authored by JENNIFER LITTON and Zhan Xu.
Connection Strength

0.521
  1. Deep Learning for Fully Automatic Tumor Segmentation on Serially Acquired Dynamic Contrast-Enhanced MRI Images of Triple-Negative Breast Cancer. Cancers (Basel). 2023 Oct 02; 15(19).
    View in: PubMed
    Score: 0.232
  2. Multiparametric MRI-based radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer. Sci Rep. 2024 07 12; 14(1):16073.
    View in: PubMed
    Score: 0.061
  3. Diffusion Tensor Imaging for Characterizing Changes in Triple-Negative Breast Cancer During Neoadjuvant Systemic Therapy. J Magn Reson Imaging. 2024 Jan 31.
    View in: PubMed
    Score: 0.059
  4. Longitudinal dynamic contrast-enhanced MRI radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer. Front Oncol. 2023; 13:1264259.
    View in: PubMed
    Score: 0.058
  5. Assessment of Response to Neoadjuvant Systemic Treatment in Triple-Negative Breast Cancer Using Functional Tumor Volumes from Longitudinal Dynamic Contrast-Enhanced MRI. Cancers (Basel). 2023 Feb 06; 15(4).
    View in: PubMed
    Score: 0.055
  6. Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRI. Sci Rep. 2023 01 20; 13(1):1171.
    View in: PubMed
    Score: 0.055
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.