Machine learning in the prediction of treatment response for emotional disorders: A systematic review and meta-analysis.

ABSTRACT:

Background

Emotional disorders such as depression and anxiety affect millions globally and pose a significant burden on public health. Personalized treatment approaches using machine learning (ML) to predict treatment response could revolutionize treatment strategies. However, there is limited evidence as to whether ML is successful in predicting treatment outcomes. This meta-analysis aims to evaluate the accuracy of ML algorithms in predicting binary treatment response (responder vs. non-responder) to evidence-based psychotherapies, pharmacotherapies, and other treatments for emotional disorders, and to examine moderators of prediction accuracy.

Methods

Following PRISMA guidelines, a comprehensive literature search was conducted across PubMed and PsycINFO from January 1st,

SUBMITTER: Curtiss J 

PROVIDER: S-EPMC12915758 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature