Improving palliative care with deep learning.

Journal: BMC medical informatics and decision making
Published Date: Dec 12, 2018

Abstract

BACKGROUND: Access to palliative care is a key quality metric which most healthcare organizations strive to improve. The primary challenges to increasing palliative care access are a combination of physicians over-estimating patient prognoses, and a shortage of palliative staff in general. This, in combination with treatment inertia can result in a mismatch between patient wishes, and their actual care towards the end of life.

Authors

  • Anand Avati
    Department of Computer Science, Stanford University, Stanford, CA, USA. avati@cs.stanford.edu.
  • Kenneth Jung
    Program in Biomedical Informatics, Stanford University, Stanford, California, USA.
  • Stephanie Harman
    Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Lance Downing
    Center for Biomedical Informatics Research, Stanford University, Stanford, CA, USA.
  • Andrew Ng
    Department of Computer Science, Stanford University, Stanford, CA, USA.
  • Nigam H Shah
    Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA, USA.

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