A Multivariable Prediction Model for Mild Cognitive Impairment and Dementia: Algorithm Development and Validation.

ABSTRACT:

Background

Mild cognitive impairment (MCI) poses significant challenges in early diagnosis and timely intervention. Underdiagnosis, coupled with the economic and social burden of dementia, necessitates more precise detection methods. Machine learning (ML) algorithms show promise in managing complex data for MCI and dementia prediction.

Objective

This study assessed the predictive accuracy of ML models in identifying the onset of MCI and dementia using the Korean Longitudinal Study of Aging (KLoSA) dataset.

Methods

This study used data from the KLoSA, a comprehensive biennial survey that tracks the demographic, health, and socioeconomic aspects of middle-aged and older Korean adults from 2018 to 2020. Among the 6171 initial households, 4975 eligible older adult partici

SUBMITTER: Oh SS 

PROVIDER: S-EPMC11624448 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature