Prediction of eating disorder treatment response trajectories via machine learning does not improve performance versus a simpler regression approach.

Journal: The International journal of eating disorders
Published Date: Jul 1, 2021

Abstract

OBJECTIVE: Patterns of response to eating disorder (ED) treatment are heterogeneous. Advance knowledge of a patient's expected course may inform precision medicine for ED treatment. This study explored the feasibility of applying machine learning to generate personalized predictions of symptom trajectories among patients receiving treatment for EDs, and compared model performance to a simpler logistic regression prediction model.

Authors

  • Hallie Espel-Huynh
    Drexel University, Philadelphia, Pennsylvania, USA.
  • Fengqing Zhang
    2 Department of Psychology, College of Arts and Sciences, Drexel University, Philadelphia, PA, USA.
  • J Graham Thomas
    Weight Control and Diabetes Research Center, The Miriam Hospital, Providence, Rhode Island, USA.
  • James F Boswell
    University at Albany-SUNY, Albany, New York, USA.
  • Heather Thompson-Brenner
    Boston University, Boston, Massachusetts, USA.
  • Adrienne S Juarascio
    Department of Psychology, WELL Center, Drexel University, Stratton Hall, 3141 Chestnut Street, Philadelphia, PA, 19104, USA.
  • Michael R Lowe
    Drexel University, Philadelphia, Pennsylvania, USA.

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