Machine learning to predict dementia for American Indian and Alaska native peoples: a retrospective cohort study.

ABSTRACT:

Background

Dementia is an increasing concern among American Indian and Alaska Native (AI/AN) communities, yet machine learning models utilizing electronic health record (EHR) data have not been developed or validated for this population. This study aimed to develop a two-year dementia risk prediction model for AI/AN individuals actively using Indian Health Service (IHS) and Tribal health services.

Methods

Seven years of data were obtained from the IHS National Data Warehouse and related EHR databases and divided into a five-year baseline period (FY2007-2011) and a two-year dementia prediction period (FY2012-2013). Four algorithms were assessed: logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO), random forest, and eXtreme Gradient Boosting (XGBoost)

SUBMITTER: Ports K 

PROVIDER: S-EPMC11875197 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature