Prediction of depression treatment outcome from multimodal data: a CAN-BIND-1 report.

ABSTRACT:

Background

Prediction of treatment outcomes is a key step in improving the treatment of major depressive disorder (MDD). The Canadian Biomarker Integration Network in Depression (CAN-BIND) aims to predict antidepressant treatment outcomes through analyses of clinical assessment, neuroimaging, and blood biomarkers.

Methods

In the CAN-BIND-1 dataset of 192 adults with MDD and outcomes of treatment with escitalopram, we applied machine learning models in a nested cross-validation framework. Across 210 analyses, we examined combinations of predictive variables from three modalities, measured at baseline and after 2 weeks of treatment, and five machine learning methods with and without feature selection. To optimize the predictors-to-observations ratio, we followed a tiered appro

SUBMITTER: Sajjadian M 

PROVIDER: S-EPMC10482706 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature