📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Predicting incident cardio-metabolic disease among persons with and without depressive and anxiety disorders: a machine learning approach. (2025)

First Author: Rydin AO

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1007/s00127-025-02857-9

PubMed Identifier: 39966164

Publication URI: http://europepmc.org/abstract/MED/39966164

Type: Journal Article/Review

Parent Publication: Social psychiatry and psychiatric epidemiology

ISSN: 0933-7954