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

Development and Evaluation of Research Methods, Instruments and Tools (209) Ubiquitous Health (uHealth) (103) Wearable Devices and Sensors (678) mHealth for Data Collection and Research (703) Machine Learning (1059) Depression and Mood Disorders; Suicide Prevention (1072) Diagnostic Tools in Mental Health (181)

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 Mullick 1 Author Orcid Image ;   Ana Radovic 2 Author Orcid Image ;   Sam Shaaban 3 Author Orcid Image ;   Afsaneh Doryab 1 Author Orcid Image
Article Authors Cited by (3) 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, US

2 Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, US

3 NuRelm, Pittsburgh, PA, US

Corresponding Author:

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