Development and classification accuracy of an automated cognitive screening tool combining working memory and connected speech tasks for early detection of cognitive impairment in primary care.

ABSTRACT:

Introduction

Cognitive screening to detect mild cognitive impairment (MCI) and dementia in primary care settings has proven to be a challenging task. The ideal solution would be a brief, yet sensitive, tool appropriate for use with individuals from diverse educational and cultural backgrounds that requires limited time and expertise from clinic staff. The purpose of this project was (1) to develop an automated cognitive screening tool incorporating cognitive and speech/language data using machine learning techniques for potential use in primary care settings and (2) to compare its classification accuracy to an established cognitive screening measure.

Methods

Participants were 53 cognitively normal and 51 cognitively impaired older adults. Each completed a working memory (WM)

SUBMITTER: Hilsabeck RC 

PROVIDER: S-EPMC12358941 | biostudies-literature | 2025 Jul-Sep

REPOSITORIES: biostudies-literature