Predicting Early Warning Signs of Psychotic Relapse From Passive Sensing Data: An Approach Using Encoder-Decoder Neural Networks.

Journal: JMIR mHealth and uHealth
Published Date: Aug 31, 2020

Abstract

BACKGROUND: Schizophrenia spectrum disorders (SSDs) are chronic conditions, but the severity of symptomatic experiences and functional impairments vacillate over the course of illness. Developing unobtrusive remote monitoring systems to detect early warning signs of impending symptomatic relapses would allow clinicians to intervene before the patient's condition worsens.

Authors

  • Daniel A Adler
    Information Science, Cornell Tech.
  • Dror Ben-Zeev
    BRiTE Center, Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.
  • Vincent W-S Tseng
    Information Science, Cornell Tech.
  • John M Kane
    The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, United States.
  • Rachel Brian
    BRiTE Center, Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States.
  • Andrew T Campbell
    Dartmouth College, Computer Science, Hanover, NH, United States.
  • Marta Hauser
    Vanguard Research Group, Glen Oaks, NY, United States.
  • Emily A Scherer
    Biomedical Data Science Department, Dartmouth Geisel School of Medicine, Hanover, NH, United States.
  • Tanzeem Choudhury
    Information Science, Cornell Tech.

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