A mixed-methods feasibility study of a novel AI-enabled, web-based, clinical decision support system for the treatment of major depression in adults

A mixed-methods feasibility study of a novel AI-enabled, web-based, clinical decision support system for the treatment of major depression in adults

Background: The objective of this paper is to discuss perceived clinical utility and impact on physician-patient relationship of a novel, artificial-intelligence (AI) enabled clinical decision support system (CDSS) for use in treating adults with major depression. Methods: A single arm, naturalistic...

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Bibliographic Details
Main Authors: Sabrina Qassim, Grace Golden, Dominique Slowey, Mary Sarfas, Kate Whitmore, Tamara Perez, Elizabeth Strong, Eryn Lundrigan, Marie-Jeanne Fradette, Jacob Baxter, Bennet Desormeau, Myriam Tanguay-Sela, Christina Popescu, Sonia Israel, Kelly Perlman, Caitrin Armstrong, Robert Fratila, Joseph Mehltretter, Karl Looper, Warren Steiner, Soham Rej, Jordan F. Karp, Katherine Heller, Sagar V. Parikh, Rebecca McGuire-Snieckus, Manuela Ferrari, Howard Margolese, David Benrimoh
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:Journal of Affective Disorders Reports
Subjects:
Clinical decision support system
Major depressive disorder
Artificial intelligence
Feasibility
Physician-patient relationship
Trust
Online Access:http://www.sciencedirect.com/science/article/pii/S2666915323002159

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http://www.sciencedirect.com/science/article/pii/S2666915323002159

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