A Mobile-Based Screening System for Data Analyses of Early Dementia Traits Detection.
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 cogniti...
| Publicado en: | Journal of Medical Systems Vol. 44; no. 1; pp. 1 - 15 |
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| Autores principales: | , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jan2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=141026230&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 141026230 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jan2020 vid: 44 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 141026230 141026230 141026230 10.1007/s10916-019-1469-0 141026230 ppf: 1 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A Mobile-Based Screening System for Data Analyses of Early Dementia Traits Detection. aug: au: Thabtah, Fadi Mampusti, Ella Peebles, David Herradura, Raymund varghese, jithin affil: Digital Technologies, Manukau Institute of Technology, Auckland, New Zealand sug: subj: Mobile Applications Health Screening Methods Dementia Diagnosis DSM Evaluation Human Male Female Middle Age Aged Aged, 80 and Over Telehealth Software Design Artificial Intelligence Cognition Disorders Diagnosis Health Informatics Data Collection Middle Aged: 45-64 years Aged: 65+ years Aged, 80 & over Male Female ab: 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. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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