A Machine Learning Approach for Early Diagnosis of Cognitive Impairment Using Population-Based Data.

ABSTRACT:

Background

The major mechanisms of dementia and cognitive impairment are vascular and neurodegenerative processes. Early diagnosis of cognitive impairment can facilitate timely interventions to mitigate progression.

Objective

This study aims to develop a reliable machine learning (ML) model using socio-demographics, vascular risk factors, and structural neuroimaging markers for early diagnosis of cognitive impairment in a multi-ethnic Asian population.

Methods

The study consisted of 911 participants from the Epidemiology of Dementia in Singapore study (aged 60- 88 years, 49.6% male). Three ML classifiers, logistic regression, support vector machine, and gradient boosting machine, were developed. Prediction results of independent classifiers were combined in a final en

SUBMITTER: Tan WY 

PROVIDER: S-EPMC9881033 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature