Detalhe da pesquisa
1.
Towards Outcome-Driven Patient Subgroups: A Machine Learning Analysis Across Six Depression Treatment Studies.
Am J Geriatr Psychiatry
; 32(3): 280-292, 2024 Mar.
Artigo
em Inglês
| MEDLINE | ID: mdl-37839909
2.
Correction: 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.
JMIR Form Res
; 8: e56570, 2024 Jan 24.
Artigo
em Inglês
| MEDLINE | ID: mdl-38266244
3.
Evaluating the perceived utility of an artificial intelligence-powered clinical decision support system for depression treatment using a simulation center.
Psychiatry Res
; 308: 114336, 2022 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-34953204
4.
Treatment selection using prototyping in latent-space with application to depression treatment.
PLoS One
; 16(11): e0258400, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-34767577
5.
Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician-patient interaction.
BJPsych Open
; 7(1): e22, 2021 Jan 06.
Artigo
em Inglês
| MEDLINE | ID: mdl-33403948
6.
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.
JMIR Form Res
; 5(10): e31862, 2021 Oct 25.
Artigo
em Inglês
| MEDLINE | ID: mdl-34694234
7.
Analysis of Features Selected by a Deep Learning Model for Differential Treatment Selection in Depression.
Front Artif Intell
; 2: 31, 2019.
Artigo
em Inglês
| MEDLINE | ID: mdl-33733120