Computational prediction of multidisciplinary team decision-making for adjuvant breast cancer drug therapies: a machine learning approach.

Journal: BMC cancer
Published Date: Dec 1, 2016

Abstract

BACKGROUND: Multidisciplinary team (MDT) meetings are used to optimise expert decision-making about treatment options, but such expertise is not digitally transferable between centres. To help standardise medical decision-making, we developed a machine learning model designed to predict MDT decisions about adjuvant breast cancer treatments.

Authors

  • Frank P Y Lin
    Department of Oncology, St Vincent's Hospital, The Kinghorn Cancer Centre, 370 Victoria St, Darlinghurst, Sydney, Australia. f.lin@unsw.edu.au.
  • Adrian Pokorny
    Department of Oncology, St Vincent's Hospital, The Kinghorn Cancer Centre, 370 Victoria St, Darlinghurst, Sydney, Australia.
  • Christina Teng
    Department of Oncology, St Vincent's Hospital, The Kinghorn Cancer Centre, 370 Victoria St, Darlinghurst, Sydney, Australia.
  • Rachel Dear
    Department of Oncology, St Vincent's Hospital, The Kinghorn Cancer Centre, 370 Victoria St, Darlinghurst, Sydney, Australia.
  • Richard J Epstein
    Department of Oncology, St Vincent's Hospital, The Kinghorn Cancer Centre, 370 Victoria St, Darlinghurst, Sydney, Australia.

Keywords

External Resources

Popular Topics
Recent Journals