Predicting mild cognitive impairment among Chinese older adults: a longitudinal study based on long short-term memory networks and machine learning.

ABSTRACT:

Background

Mild cognitive impairment (MCI) is a transitory yet reversible stage of dementia. Systematic, scientific and population-wide early screening system for MCI is lacking. This study aimed to construct prediction models using longitudinal data to identify potential MCI patients and explore its critical features among Chinese older adults.

Methods

A total of 2,128 participants were selected from wave 5-8 of Chinese Longitudinal Healthy Longevity Study. Cognitive function was measured using the Chinese version of Mini-Mental State Examination. Long- short-term memory (LSTM) and three machine learning techniques, including 8 sociodemographic features and 12 health behavior and health status features, were used to predict individual risk of MCI in the next year. Performan

SUBMITTER: Huang Y 

PROVIDER: S-EPMC10626462 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature