Artificial image objects for classification of breast cancer biomarkers with transcriptome sequencing data and convolutional neural network algorithms.

Journal: Breast cancer research : BCR
Published Date: Oct 10, 2021

Abstract

BACKGROUND: Transcriptome sequencing has been broadly available in clinical studies. However, it remains a challenge to utilize these data effectively for clinical applications due to the high dimension of the data and the highly correlated expression between individual genes.

Authors

  • Xiangning Chen
    410 AI, LLC, Germantown, MD, 20876, USA. va.samchen@gmail.com.
  • Daniel G Chen
    410 AI, LLC, Germantown, MD, 20876, USA.
  • Zhongming Zhao
    Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, United States.
  • Justin M Balko
    Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.
  • Jingchun Chen
    Nevada Institute of Personalized Medicine, University of Nevada Las Vegas, Las Vegas, NV, 89154, USA. Jingchun.chen@unlv.edu.

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