Ontology highlight
ABSTRACT: Background
Sarcopenia significantly increases the risk of cognitive impairments in older adults. Early detection of mild cognitive impairment (MCI) in individuals with sarcopenia is essential for timely intervention.Aims
To develop an accurate prediction model for screening MCI in individuals with sarcopenia.Methods
We employed machine learning and deep learning techniques to analyze data from 570 patients with sarcopenia from the China Health and Retirement Longitudinal Study (CHARLS). Our model forecasts MCI incidence over the next four years, categorizing patients into low and high-risk groups based on their risk levels.Results
The model was constructed using CHARLS data from 2011 to 2015, incorporating eight validated variables. It outperformed logistic
SUBMITTER: Liu X
PROVIDER: S-EPMC11889009 | biostudies-literature | 2025 Mar
REPOSITORIES: biostudies-literature