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

Formative Evaluation of Digital Health Interventions (2193) Depression and Mood Disorders; Suicide Prevention (1271) Artificial Intelligence (1186) mHealth for Diagnosis (48) Diagnostic Tools in Mental Health (220) Longitudinal and Cohort Studies in Public Health (254) Decision Support for Health Professionals (1127) Clinical Information and Decision Making (1314)

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

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 Author Orcid Image ;   Grace Golden2 Author Orcid Image ;   David Benrimoh1 Author Orcid Image ;   Myriam Tanguay-Sela1 Author Orcid Image ;   Dominique Slowey3 Author Orcid Image ;   Eryn Lundrigan3 Author Orcid Image ;   Jérôme Williams3 Author Orcid Image ;   Bennet Desormeau3 Author Orcid Image ;   Divyesh Kardani1 Author Orcid Image ;   Tamara Perez3 Author Orcid Image ;   Colleen Rollins4 Author Orcid Image ;   Sonia Israel1 Author Orcid Image ;   Kelly Perlman1, 3 Author Orcid Image ;   Caitrin Armstrong1 Author Orcid Image ;   Jacob Baxter3 Author Orcid Image ;   Kate Whitmore3 Author Orcid Image ;   Marie-Jeanne Fradette3 Author Orcid Image ;   Kaelan Felcarek-Hope3 Author Orcid Image ;   Ghassen Soufi3 Author Orcid Image ;   Robert Fratila1 Author Orcid Image ;   Joseph Mehltretter3 Author Orcid Image ;   Karl Looper3 Author Orcid Image ;   Warren Steiner3 Author Orcid Image ;   Soham Rej3 Author Orcid Image ;   Jordan F Karp5 Author Orcid Image ;   Katherine Heller6 Author Orcid Image ;   Sagar V Parikh7 Author Orcid Image ;   Rebecca McGuire-Snieckus8 Author Orcid Image ;   Manuela Ferrari9 Author Orcid Image ;   Howard Margolese3 Author Orcid Image ;   Gustavo Turecki9 Author Orcid Image
Article Authors Cited by (14) Tweetations (6) Metrics

Journals

  1. Shen J, Golchi S, Moodie E, Benrimoh D. Bayesian group sequential designs for cluster‐randomized trials. Stat 2022;11(1) View
  2. Tanguay-Sela M, Rollins C, Perez T, Qiang V, Golden G, Tunteng J, Perlman K, Simard J, Benrimoh D, Margolese H. A systematic meta-review of patient-level predictors of psychological therapy outcome in major depressive disorder. Journal of Affective Disorders 2022;317:307 View
  3. Higgins O, Short B, Chalup S, Wilson R. Artificial intelligence (AI) and machine learning (ML) based decision support systems in mental health: An integrative review. International Journal of Mental Health Nursing 2023;32(4):966 View
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  5. Benrimoh D, Kleinerman A, Furukawa T, III C, Lenze E, Karp J, Mulsant B, Armstrong C, Mehltretter J, Fratila R, Perlman K, Israel S, Popescu C, Golden G, Qassim S, Anacleto A, Tanguay-Sela M, Kapelner A, Rosenfeld A, Turecki G. Towards Outcome-Driven Patient Subgroups: A Machine Learning Analysis Across Six Depression Treatment Studies. The American Journal of Geriatric Psychiatry 2024;32(3):280 View
  6. Sehrawat O, Noseworthy P, Siontis K, Haddad T, Halamka J, Liu H. Data-Driven and Technology-Enabled Trial Innovations Toward Decentralization of Clinical Trials: Opportunities and Considerations. Mayo Clinic Proceedings 2023;98(9):1404 View
  7. Qassim S, Golden G, Slowey D, Sarfas M, Whitmore K, Perez T, Strong E, Lundrigan E, Fradette M, Baxter J, Desormeau B, Tanguay-Sela M, Popescu C, Israel S, Perlman K, Armstrong C, Fratila R, Mehltretter J, Looper K, Steiner W, Rej S, Karp J, Heller K, Parikh S, McGuire-Snieckus R, Ferrari M, Margolese H, Benrimoh D. A mixed-methods feasibility study of a novel AI-enabled, web-based, clinical decision support system for the treatment of major depression in adults. Journal of Affective Disorders Reports 2023;14:100677 View
  8. Benrimoh D, Fisher V, Mourgues C, Sheldon A, Smith R, Powers A. Barriers and solutions to the adoption of translational tools for computational psychiatry. Molecular Psychiatry 2023;28(6):2189 View
  9. Bellón J, Rodríguez-Morejón A, Conejo-Cerón S, Campos-Paíno H, Rodríguez-Bayón A, Ballesta-Rodríguez M, Rodríguez-Sánchez E, Mendive J, López del Hoyo Y, Luna J, Tamayo-Morales O, Moreno-Peral P. A personalized intervention to prevent depression in primary care based on risk predictive algorithms and decision support systems: protocol of the e-predictD study. Frontiers in Psychiatry 2023;14 View
  10. Golden G, Popescu C, Israel S, Perlman K, Armstrong C, Fratila R, Tanguay-Sela M, Benrimoh D. Applying artificial intelligence to clinical decision support in mental health: What have we learned?. Health Policy and Technology 2024;13(2):100844 View
  11. Giddings R, Joseph A, Callender T, Janes S, van der Schaar M, Sheringham J, Navani N. Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review. The Lancet Digital Health 2024;6(2):e131 View
  12. Evans R, Bryant L, Russell G, Absolom K. Trust and acceptability of data-driven clinical recommendations in everyday practice: A scoping review. International Journal of Medical Informatics 2024;183:105342 View
  13. Perlman K, Mehltretter J, Benrimoh D, Armstrong C, Fratila R, Popescu C, Tunteng J, Williams J, Rollins C, Golden G, Turecki G. Development of a differential treatment selection model for depression on consolidated and transformed clinical trial datasets. Translational Psychiatry 2024;14(1) View