Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning.

ABSTRACT: Psychosocial and stress-related factors (PSFs), defined as internal or external stimuli that induce biological changes, are potentially modifiable factors and accessible targets for interventions that are associated with adverse pregnancy outcomes (APOs). Although individual APOs have been shown to be connected to PSFs, they are biologically interconnected, relatively infrequent, and therefore challenging to model. In this context, multi-task machine learning (MML) is an ideal tool for exploring the interconnectedness of APOs on the one hand and building on joint combinatorial outcomes to increase predictive power on the other hand. Additionally, by integrating single cell immunological profiling of underlying biological processes, the effects of stress-based therapeutics may be measurable

SUBMITTER: Becker M 

PROVIDER: S-EPMC9793100 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature