This paper is in the following e-collection/theme issue:

Digital Health Reviews (1742) Mobile Health (mhealth) (3491) Bipolar Disorders (74) Diagnostic Tools in Mental Health (328) Digital Biomarkers and Digital Phenotyping (291) Depression and Mood Disorders; Suicide Prevention (1703) Fitness Trackers and Smart Pedometers/Accelerometers (673)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72229, first published .
Using Digital Phenotyping to Discriminate Unipolar Depression and Bipolar Disorder: Systematic Review

Using Digital Phenotyping to Discriminate Unipolar Depression and Bipolar Disorder: Systematic Review

Using Digital Phenotyping to Discriminate Unipolar Depression and Bipolar Disorder: Systematic Review

Authors of this article:

Rongrong Zhong1 Author Orcid Image ;   XiaoHui Wu1 Author Orcid Image ;   Jun Chen1 Author Orcid Image ;   Yiru Fang2, 3, 4 Author Orcid Image
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Saxena A, Saxena S, Saxena Y, Jain A, Goyal P, Kumar A, Mishra S, Kumar S. Bipolar Disorder in the Era of Precision Psychiatry: Biomarkers, Digital Innovations, and Global Challenges. Journal for Research in Applied Sciences and Biotechnology 2025;4(5):1 View
  2. Diler R, Vahedifard F, Birmaher B, Iyengar S, Wolfe M, Lepore B, Chobany M, Abdul-Waalee H, Malgireddy G, Hart J, Bertocci M. Differentiating Pediatric Bipolar Disorder, Attention-Deficit/Hyperactivity Disorder, and Other Psychopathologies Using Self-Reported Mood and Energy Data and Actigraphy Findings: Correlation and Machine Learning–Based Prediction of Mood Severity. JMIR Mental Health 2025;12:e78163 View