Incorporating end-user perspectives into the development of a machine learning algorithm for first time perinatal depression prediction.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Jul 1, 2025

Abstract

OBJECTIVE: Machine learning algorithms can advance clinical care, including identifying mental health conditions. These algorithms are often developed without considering the perspectives of the affected populations. This study describes the process of incorporating end-user perspectives into the development and implementation planning of a prediction algorithm for new perinatal depression onset.

Authors

  • Kelly Williams
    UPMC Center for High-Value Health Care, Pittsburgh, PA 15219, United States.
  • Cara Nikolajski
    UPMC Center for High-Value Health Care, Pittsburgh, PA 15219, United States.
  • Samantha Rodriguez
    Division of General Internal Medicine, University of Pittsburgh, 230 McKee Pl, Suite 600, Pittsburgh, PA, 15213, USA.
  • Elaine Kwok
    UPMC Center for High-Value Health Care, Pittsburgh, PA 15219, United States.
  • Priya Gopalan
    UPMC Western Psychiatric Hospital, Pittsburgh, PA, 15213, USA.
  • Hyagriv Simhan
    Department of Obstetrics, Gynecology, and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA.
  • Tamar Krishnamurti
    Division of General Internal Medicine, University of Pittsburgh, 230 McKee Pl, Suite 600, Pittsburgh, PA, 15213, USA. tamark@pitt.edu.

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