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

Viewpoints and Perspectives (575) Digital Biomarkers and Digital Phenotyping (231) Wearable Devices and Sensors (1015) mHealth for Data Collection and Research (1093)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39546, first published .
A Call to Expand the Scope of Digital Phenotyping

A Call to Expand the Scope of Digital Phenotyping

A Call to Expand the Scope of Digital Phenotyping

Authors of this article:

Christopher De Boer1 Author Orcid Image ;   Hassan Ghomrawi1, 2, 3 Author Orcid Image ;   Suhail Zeineddin1 Author Orcid Image ;   Samuel Linton1 Author Orcid Image ;   Soyang Kwon4 Author Orcid Image ;   Fizan Abdullah1 Author Orcid Image
Article Authors Cited by (5) Tweetations (7) Metrics

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  3. Wierenga H, Pagoni K, Skalkidou A, Papadopoulos F, Geusens F. Dropping out of a peripartum depression mHealth study: participants’ motives and suggestions for improvement. BMC Medical Research Methodology 2025;25(1) View
  4. Jeong J, Jeon Y, Kim H, Yeom J, Shin Y, Kim S, Pack S, Lee H, Cheong T, Cho C. Machine learning-based prediction of restless legs syndrome using digital phenotypes from wearables and smartphone data. Scientific Reports 2025;15(1) View

Conference Proceedings

  1. Zamudio L, Monarca I, Favela J, Tentori M. Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing. Towards using Digital Phenotypes in Mobile Tactile Stimulation for Children with ASD View