This paper is in the following e-collection/theme issue:
Formative Evaluation of Digital Health Interventions (2410) Depression and Mood Disorders; Suicide Prevention (1363) Artificial Intelligence (1371) mHealth for Diagnosis (60) Diagnostic Tools in Mental Health (242) Longitudinal and Cohort Studies in Public Health (309) Decision Support for Health Professionals (1185) Clinical Information and Decision Making (1407)Published on in Vol 5, No 10 (2021): October
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/31862, first published
.
Evaluating the Clinical Feasibility of an Artificial Intelligence–Powered, Web-Based Clinical Decision Support System for the Treatment of Depression in Adults: Longitudinal Feasibility Study
Evaluating the Clinical Feasibility of an Artificial Intelligence–Powered, Web-Based Clinical Decision Support System for the Treatment of Depression in Adults: Longitudinal Feasibility Study
Authors of this article:
Christina Popescu1 ; Grace Golden2 ; David Benrimoh1 ; Myriam Tanguay-Sela1 ; Dominique Slowey3 ; Eryn Lundrigan3 ; Jérôme Williams3 ; Bennet Desormeau3 ; Divyesh Kardani1 ; Tamara Perez3 ; Colleen Rollins4 ; Sonia Israel1 ; Kelly Perlman1, 3 ; Caitrin Armstrong1 ; Jacob Baxter3 ; Kate Whitmore3 ; Marie-Jeanne Fradette3 ; Kaelan Felcarek-Hope3 ; Ghassen Soufi3 ; Robert Fratila1 ; Joseph Mehltretter3 ; Karl Looper3 ; Warren Steiner3 ; Soham Rej3 ; Jordan F Karp5 ; Katherine Heller6 ; Sagar V Parikh7 ; Rebecca McGuire-Snieckus8 ; Manuela Ferrari9 ; Howard Margolese3 ; Gustavo Turecki9
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