Predicting conversion to psychosis using machine learning: response to Cannon.

Journal: Frontiers in psychiatry
Published Date: Jan 15, 2025

Abstract

BACKGROUND: We previously reported that machine learning could be used to predict conversion to psychosis in individuals at clinical high risk (CHR) for psychosis with up to 90% accuracy using the North American Prodrome Longitudinal Study-3 (NAPLS-3) dataset. A definitive test of our predictive model that was trained on the NAPLS-3 data, however, requires further support through implementation in an independent dataset. In this report we tested for model generalization using the previous iteration of NAPLS-3, the NAPLS-2, using the identical machine learning algorithms employed in our previous study.

Authors

  • Jason Smucny
    Department of Psychiatry, University of California, Davis, Davis, CA, United States.
  • Tyrone D Cannon
    Department of Psychology, Yale University, New Haven, CT, United States.
  • Carrie E Bearden
    Department of Psychiatry, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States.
  • Jean Addington
    Department of Psychiatry, University of Calgary, Calgary, AB, Canada.
  • Kristen S Cadenhead
    Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC, United States.
  • Barbara A Cornblatt
    Department of Psychiatry Research, Zucker Hillside Hospital, New York, NY, United States.
  • Matcheri Keshavan
    Department of Psychiatry, Harvard University, Cambridge, MA, United States.
  • Daniel H Mathalon
    Department of Psychiatry, University of California, San Francisco, San Francisco, CA, United States.
  • Diana O Perkins
    Department of Psychiatry, University of San Diego, San Diego, CA, United States.
  • William Stone
    Department of Psychiatry, Harvard University, Cambridge, MA, United States.
  • Elaine F Walker
    Department of Psychiatry, Emory University, Atlanta, GA, United States.
  • Scott W Woods
    Department of Psychology, Yale University, New Haven, CT, United States.
  • Ian Davidson
    Department of Computer Science, University of California, Davis, Davis, CA, United States.
  • Cameron S Carter
    Department of Psychiatry, University of California, Irvine, Irvine, CA, United States.

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