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Evaluating the Machine Learning Literature: A Primer and User's Guide for Psychiatrists

Adrienne Grzenda1, Nina V Kraguljac1, William M McDonald1

  • 1Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, and Olive View-UCLA Medical Center, Sylmar (Grzenda); Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Kraguljac); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald); Department of Psychiatry, University of Texas Dell Medical School, Austin (Nemeroff); Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston (Torous); Department of Psychiatry and Behavioral Sciences, Albert Einstein School of Medicine, Bronx, N.Y. (Alpert); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, Calif., and Veterans Affairs Palo Alto Health Care System, Palo Alto, Calif. (Rodriguez); Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis (Widge).

The American Journal of Psychiatry
|June 3, 2021
PubMed
Summary

No abstract available in PubMed .

Keywords:
Academic PsychiatryComputersMachine Learning

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