Population modeling with machine learning can enhance measures of mental health.

ABSTRACT:

Background

Biological aging is revealed by physical measures, e.g., DNA probes or brain scans. In contrast, individual differences in mental function are explained by psychological constructs, e.g., intelligence or neuroticism. These constructs are typically assessed by tailored neuropsychological tests that build on expert judgement and require careful interpretation. Could machine learning on large samples from the general population be used to build proxy measures of these constructs that do not require human intervention?

Results

Here, we built proxy measures by applying machine learning on multimodal MR images and rich sociodemographic information from the largest biomedical cohort to date: the UK Biobank. Objective model comparisons revealed that all proxies captured t

SUBMITTER: Dadi K 

PROVIDER: S-EPMC8559220 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature