Machine learning and big data: Implications for disease modeling and therapeutic discovery in psychiatry.

Journal: Artificial intelligence in medicine
Published Date:

Abstract

INTRODUCTION: Machine learning capability holds promise to inform disease models, the discovery and development of novel disease modifying therapeutics and prevention strategies in psychiatry. Herein, we provide an introduction on how machine learning/Artificial Intelligence (AI) may instantiate such capabilities, as well as provide rationale for its application to psychiatry in both research and clinical ecosystems.

Authors

  • Andy M Y Tai
    Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada.
  • Alcides Albuquerque
    Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada.
  • Nicole E Carmona
    Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada.
  • Mehala Subramanieapillai
    Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada.
  • Danielle S Cha
    Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada.
  • Margarita Sheko
    Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada.
  • Yena Lee
    Institute of Medical Science, University of Toronto, Toronto, Canada; Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, Canada; Brain and Cognition Discovery Foundation, Toronto, Canada.
  • Rodrigo Mansur
    Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada.
  • Roger S McIntyre
    Institute of Medical Science, University of Toronto, Toronto, Canada; Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, Canada; Brain and Cognition Discovery Foundation, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada; Department of Pharmacology, University of Toronto, Toronto, Canada. Electronic address: Roger.McIntyre@uhn.ca.