Using Machine Learning to Predict Cognitive Impairment Among Middle-Aged and Older Chinese: A Longitudinal Study.

ABSTRACT: Objective: To explore the predictive value of machine learning in cognitive impairment, and identify important factors for cognitive impairment. Methods: A total of 2,326 middle-aged and elderly people completed questionnaire, and physical examination evaluation at baseline, Year 2, and Year 4 follow-ups. A random forest machine learning (ML) model was used to predict the cognitive impairment at Year 2 and Year 4 longitudinally. Based on Year 4 cross-sectional data, the same method was applied to establish a prediction model and verify its longitudinal prediction accuracy for cognitive impairment. Meanwhile, the ability of random forest and traditional logistic regression model to longitudinally predict 2-year and 4-year cognitive impairment was compared. Results: Rand

SUBMITTER: Liu H 

PROVIDER: S-EPMC9926933 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature