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.
Original language | English |
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Article number | 24 |
Number of pages | 14 |
Journal | Journal of Medical Systems |
Volume | 44 |
Issue number | 1 |
Early online date | 11 Dec 2019 |
DOIs | |
Publication status | Published - 1 Jan 2020 |
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David Peebles
- School of Human and Health Sciences - Professor
- The Centre for Cognition and Neuroscience - Director
- Department of Social and Psychological Sciences - Professor
Person: Academic