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Articles Published Processes
3/18/2022 12:26:44 PM | Browse: 421 | Download: 704
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Received |
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2021-06-30 02:12 |
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Peer-Review Started |
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2021-06-30 02:16 |
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To Make the First Decision |
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Return for Revision |
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2021-09-05 20:59 |
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Revised |
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2021-09-23 14:42 |
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Second Decision |
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2022-02-11 05:52 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2022-02-13 17:04 |
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Articles in Press |
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2022-02-13 17:04 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2022-03-11 08:50 |
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Publish the Manuscript Online |
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2022-03-18 12:26 |
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. |
Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
Website |
http://www.wjgnet.com |
Category |
Psychiatry |
Manuscript Type |
Minireviews |
Article Title |
Digital phenotyping in depression diagnostics: Integrating psychiatric and engineering perspectives
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Manuscript Source |
Invited Manuscript |
All Author List |
Jayesh Kamath, Roberto Leon Barriera, Neha Jain, Efraim Keisari and Bing Wang |
ORCID |
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Funding Agency and Grant Number |
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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. |
Publish Date |
2022-03-18 12:26 |
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 |
URL |
https://www.wjgnet.com/2220-3206/full/v12/i3/393.htm |
DOI |
https://dx.doi.org/10.5498/wjp.v12.i3.393 |
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