Predicting the presence of depressive symptoms in the HIV-HCV co-infected population in Canada using supervised machine learning.

ABSTRACT:

Background

Depression is common in the human immunodeficiency virus (HIV)-hepatitis C virus (HCV) co-infected population. Demographic, behavioural, and clinical data collected in research settings may be of help in identifying those at risk for clinical depression. We aimed to predict the presence of depressive symptoms indicative of a risk of depression and identify important classification predictors using supervised machine learning.

Methods

We used data from the Canadian Co-infection Cohort, a multicentre prospective cohort, and its associated sub-study on Food Security (FS). The Center for Epidemiologic Studies Depression Scale-10 (CES-D-10) was administered in the FS sub-study; participants were classified as being at risk for clinical depression if scores ≥ 10. We dev

SUBMITTER: Marathe G 

PROVIDER: S-EPMC9375382 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature