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

Development and Evaluation of Research Methods, Instruments and Tools (511) Ubiquitous Health (uHealth) (125) Wearable Devices and Sensors (903) mHealth for Data Collection and Research (981) Machine Learning (1501) Depression and Mood Disorders; Suicide Prevention (1392) Diagnostic Tools in Mental Health (248)

Published on in Vol 6, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35807, first published .
Predicting Depression in Adolescents Using Mobile and Wearable Sensors: Multimodal Machine Learning–Based Exploratory Study

Predicting Depression in Adolescents Using Mobile and Wearable Sensors: Multimodal Machine Learning–Based Exploratory Study

Predicting Depression in Adolescents Using Mobile and Wearable Sensors: Multimodal Machine Learning–Based Exploratory Study

Authors of this article:

Tahsin Mullick1 Author Orcid Image ;   Ana Radovic2 Author Orcid Image ;   Sam Shaaban3 Author Orcid Image ;   Afsaneh Doryab1 Author Orcid Image
Article Authors Cited by (31) Tweetations (4) Metrics

Tahsin Mullick   1 , MEng ;   Ana Radovic   2 , MD, MSc ;   Sam Shaaban   3 , MBA ;   Afsaneh Doryab   1 , PhD

1 Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA, United States

2 Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, United States

3 NuRelm, Pittsburgh, PA, United States

Corresponding Author:

  • Tahsin Mullick, MEng
  • Department of Engineering Systems and Environment
  • University of Virginia
  • Olsson Hall, 151 Engineer's Way
  • Charlottesville, VA, 22904
  • United States
  • Phone: 1 434 243 5823
  • Email: tum7q@virginia.edu