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Personalized treatment selection in routine care: Integrating machine learning and statistical algorithms to recommend cognitive behavioral or psychodynamic therapy.

Objective: This study aims at developing a treatment selection algorithm using a combination of machine learning and statistical inference to recommend patients' optimal treatment based on their pre-treatment characteristics. Methods: A disorder-heterogeneous, naturalistic sample of N = 1,379 outpat...

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Publicado en:Psychotherapy Research Vol. 31; no. 1; pp. 33 - 52
Autores principales: Schwartz, Brian, Cohen, Zachary D., Rubel, Julian A., Zimmermann, Dirk, Wittmann, Werner W., Lutz, Wolfgang
Formato: Artículo
Publicado: Taylor & Francis Ltd Jan2021
Materias:
Cognitive therapy
Patient selection
Statistical learning
Machine learning
Behavior therapists
Psychodynamic psychotherapy
Random forest algorithms
Acceso en línea:Ver este registro en EBSCOhost