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Connection

Hui Li to Middle Aged

This is a "connection" page, showing publications Hui Li has written about Middle Aged.
Connection Strength

0.233
  1. Digital Mammography in Breast Cancer: Additive Value of Radiomics of Breast Parenchyma. Radiology. 2019 04; 291(1):15-20.
    View in: PubMed
    Score: 0.042
  2. MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays. Radiology. 2016 Nov; 281(2):382-391.
    View in: PubMed
    Score: 0.035
  3. Computerized analysis of mammographic parenchymal patterns on a large clinical dataset of full-field digital mammograms: robustness study with two high-risk datasets. J Digit Imaging. 2012 Oct; 25(5):591-8.
    View in: PubMed
    Score: 0.027
  4. Fractal analysis of mammographic parenchymal patterns in breast cancer risk assessment. Acad Radiol. 2007 May; 14(5):513-21.
    View in: PubMed
    Score: 0.019
  5. Computerized texture analysis of mammographic parenchymal patterns of digitized mammograms. Acad Radiol. 2005 Jul; 12(7):863-73.
    View in: PubMed
    Score: 0.016
  6. Differences in Molecular Subtype Reference Standards Impact AI-based Breast Cancer Classification with Dynamic Contrast-enhanced MRI. Radiology. 2023 04; 307(1):e220984.
    View in: PubMed
    Score: 0.014
  7. Independent validation of machine learning in diagnosing breast Cancer on magnetic resonance imaging within a single institution. Cancer Imaging. 2019 Sep 18; 19(1):64.
    View in: PubMed
    Score: 0.011
  8. Radiomics robustness assessment and classification evaluation: A two-stage method demonstrated on multivendor FFDM. Med Phys. 2019 May; 46(5):2145-2156.
    View in: PubMed
    Score: 0.011
  9. Transfer Learning From Convolutional Neural Networks for Computer-Aided Diagnosis: A Comparison of Digital Breast Tomosynthesis and Full-Field Digital Mammography. Acad Radiol. 2019 06; 26(6):735-743.
    View in: PubMed
    Score: 0.010
  10. Most-enhancing tumor volume by MRI radiomics predicts recurrence-free survival "early on" in neoadjuvant treatment of breast cancer. Cancer Imaging. 2018 Apr 13; 18(1):12.
    View in: PubMed
    Score: 0.010
  11. Using computer-extracted image phenotypes from tumors on breast magnetic resonance imaging to predict breast cancer pathologic stage. Cancer. 2016 Mar 01; 122(5):748-57.
    View in: PubMed
    Score: 0.008
  12. Relationships between computer-extracted mammographic texture pattern features and BRCA1/2 mutation status: a cross-sectional study. Breast Cancer Res. 2014; 16(4):424.
    View in: PubMed
    Score: 0.008
  13. Combined use of T2-weighted MRI and T1-weighted dynamic contrast-enhanced MRI in the automated analysis of breast lesions. Magn Reson Med. 2011 Aug; 66(2):555-64.
    View in: PubMed
    Score: 0.006
  14. Normal parenchymal enhancement patterns in women undergoing MR screening of the breast. Eur Radiol. 2011 Jul; 21(7):1374-82.
    View in: PubMed
    Score: 0.006
  15. Cancerous breast lesions on dynamic contrast-enhanced MR images: computerized characterization for image-based prognostic markers. Radiology. 2010 Mar; 254(3):680-90.
    View in: PubMed
    Score: 0.006
  16. Comparison of radiographic texture analysis from computed radiography and bone densitometry systems. Med Phys. 2004 Apr; 31(4):882-91.
    View in: PubMed
    Score: 0.004
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.