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Updated: Jan 2, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
A Mobile-Based Screening System for Data Analyses of Early Dementia Traits Detection
Fadi Thabtah1, Ella Mampusti2, David Peebles3
1Digital Technologies, Manukau Institute of Technology, Auckland, New Zealand. fadi.fayez@manukau.ac.nz.
Abstract:
Existing early detection methods that deal with the pre-diagnosis of dementia have been criticised as not being comprehensive as they do not measure certain cognitive functioning domains besides being inaccessible. A more realistic approach is to develop a comprehensive outcome that includes cognitive functioning of dementia, as this will offer a robust and unbiased outcome for an individual. In this research, a mobile screening application for dementia traits called DementiaTest is proposed, which adopts the gold standard assessment criteria of Diagnostic and Statistical Manual of Mental Disorders (DSM-V). DementiaTest is implemented and tested on the Android and IOS stores. More importantly, it collects data from cases and controls using an easy, interactive, and accessible platform. It provides patients and their family with quick pre-diagnostic reports using certain cognitive functioning indicators; these can be utilized by general practitioners (GPs) for referrals for further assessment in cases of positive outcomes. The data gathered using the new application can be analysed using Artificial Intelligence methods to evaluate the performance of the screening to pinpoint early signs of the dementia.
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