Machine learning-based predictive models for the occurrence of behavioral and psychological symptoms of dementia: model development and validation.

ABSTRACT: The behavioral and psychological symptoms of dementia (BPSD) are challenging aspects of dementia care. This study used machine learning models to predict the occurrence of BPSD among community-dwelling older adults with dementia. We included 187 older adults with dementia for model training and 35 older adults with dementia for external validation. Demographic and health data and premorbid personality traits were examined at the baseline, and actigraphy was utilized to monitor sleep and activity levels. A symptom diary tracked caregiver-perceived symptom triggers and the daily occurrence of 12 BPSD classified into seven subsyndromes. Several prediction models were also employed, including logistic regression, random forest, gradient boosting machine, and support vector machine. The random

SUBMITTER: Cho E 

PROVIDER: S-EPMC10195861 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature