DeepTRIAGE: interpretable and individualised biomarker scores using attention mechanism for the classification of breast cancer sub-types.

Journal: BMC medical genomics
Published Date:

Abstract

BACKGROUND: Breast cancer is a collection of multiple tissue pathologies, each with a distinct molecular signature that correlates with patient prognosis and response to therapy. Accurately differentiating between breast cancer sub-types is an important part of clinical decision-making. Although this problem has been addressed using machine learning methods in the past, there remains unexplained heterogeneity within the established sub-types that cannot be resolved by the commonly used classification algorithms.

Authors

  • Adham Beykikhoshk
    Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, Australia. adham.beyki@deakin.edu.au.
  • Thomas P Quinn
    Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, Australia.
  • Samuel C Lee
    Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong, Australia.
  • Truyen Tran
    Centre for Pattern Recognition and Data Analytics, School of Information Technology, Deakin University, Geelong, Victoria, Australia.
  • Svetha Venkatesh
    Applied Artificial Intelligence Institute, Deakin University, Melbourne, Australia.