Identifying Comorbidity Patterns in People with and without Alzheimer's Disease Using Latent Dirichlet Allocation.

ABSTRACT:

Background

Multimorbidity is common in older adults and complicates diagnosing and care for this population.

Objective

We investigated co-occurrence patterns (clustering) of medical conditions in persons with Alzheimer's disease (AD) and their matched controls.

Methods

The register-based Medication use and Alzheimer's disease study (MEDALZ) includes 70,718 community-dwelling persons with incident AD diagnosed during 2005-2011 in Finland and a matched comparison cohort. Latent Dirichlet Allocation was used to cluster the comorbidities (ICD-10 diagnosis codes). Modeling was performed separately for AD and control cohorts. We experimented with different numbers of clusters (also known as topics in the field of Natural Language Processing) ranging from five to 20.

Resu

SUBMITTER: Rajamaki B 

PROVIDER: S-EPMC11492117 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature