Improving Cardiovascular Disease Prediction With Machine Learning Using Mental Health Data: A Prospective UK Biobank Study.

ABSTRACT:

Background

Robust and accurate prediction of cardiovascular disease (CVD) risk facilitates early intervention to benefit patients. The intricate relationship between mental health disorders and CVD is widely recognized. However, existing models often overlook psychological factors, relying on a limited set of clinical and lifestyle parameters, or being developed on restricted population subsets.

Objectives

This study aims to assess the impact of integrating psychological data into a novel machine learning (ML) approach on enhancing CVD prediction performance.

Methods

Using a comprehensive UK Biobank data set (n = 375,145), the correlation between CVD and traditional and psychological risk factors was examined. CVD included hypertensive disease, ischemic heart disease,

SUBMITTER: Dorraki M 

PROVIDER: S-EPMC11450915 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature