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Publication Name World Journal of Psychiatry
Manuscript ID 69286
Country United States
Category Psychiatry
Manuscript Type Minireviews
Article Title Digital phenotyping in depression diagnostics: Integrating psychiatric and engineering perspectives
Manuscript Source Invited Manuscript
All Author List Jayesh Kamath, Roberto Leon Barriera, Neha Jain, Efraim Keisari and Bing Wang
Funding Agency and Grant Number
Corresponding Author Jayesh Kamath, MD, PhD, Professor, Department of Psychiatry & Department of Immunology, University of Connecticut School of Medicine, University of Connecticut Health Center , 263 Farmington avenue , Farmington, CT 06030, United States. jkamath@uchc.edu
Key Words Digital phenotyping; Depression; Ecological momentary assessment; Telepsychiatry; Passive sensing; Smart phone
Core Tip There are systematic/quantitative reviews and meta-analyses of digital phenotyping (DP) in depression available in literature. These reviews are primarily published by engineering groups and provide limited psychiatric perspective, especially clinical relevance and clinical integration. The current review presents an overview of digital phenotyping of depression diagnostics and assessment from both psychiatric and engineering perspective. The overview includes major advances in the field of DP of depression diagnostics including active and passive ecological momentary assessment, DP using data from social media, and DP using data from electronic medical records. We briefly discuss investigations conducted by our group and present a model for clinical integration of DP informed by those investigations conducted by our group. Finally, we discuss benefits, challenges, and opportunities pertaining to clinical integration of DP of depression diagnostics from interdisciplinary perspective.
Citation Kamath J, Leon Barriera R, Jain N, Keisari E, Wang B. Digital Phenotyping in Depression Diagnostics: Integrating Psychiatric and Engineering Perspectives. World J Psychiatr 2022; 12(3): 393-409
Received
2021-06-30 02:12
Peer-Review Started
2021-06-30 02:16
To Make the First Decision
Return for Revision
2021-09-05 20:59
Revised
2021-09-23 14:42
Second Decision
2022-02-11 05:52
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2022-02-13 17:04
Articles in Press
2022-02-13 17:04
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
2022-03-11 08:50
ISSN 2220-3206 (online)
Open Access This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
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