EXIST: EXamining rIsk of excesS adiposiTy-Machine learning to predict obesity-related complications.

ABSTRACT:

Background

Obesity is associated with an increased risk of multiple conditions, ranging from heart disease to cancer. However, there are few predictive models for these outcomes that have been developed specifically for people with overweight/obesity.

Objective

To develop predictive models for obesity-related complications in patients with overweight and obesity.

Methods

Electronic health record data of adults with body mass index 25-80 kg/m² treated in primary care practices between 2000 and 2019 were utilized to develop and evaluate predictive models for nine long-term clinical outcomes using a) Lasso-Cox models and b) a machine-learning method random survival forests (RSF). Models were trained on a training dataset and evaluated on a test dataset over 10

SUBMITTER: Turchin A 

PROVIDER: S-EPMC10804333 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature