Literature DB >> 32961306

Dementia medical screening using mobile applications: A systematic review with a new mapping model.

Fadi Thabtah1, David Peebles2, Jenny Retzler3, Chanchala Hathurusingha4.   

Abstract

Early detection is the key to successfully tackling dementia, a neurocognitive condition common among the elderly. Therefore, screening using technological platforms such as mobile applications (apps) may provide an important opportunity to speed up the diagnosis process and improve accessibility. Due to the lack of research into dementia diagnosis and screening tools based on mobile apps, this systematic review aims to identify the available mobile-based dementia and mild cognitive impairment (MCI) apps using specific inclusion and exclusion criteria. More importantly, we critically analyse these tools in terms of their comprehensiveness, validity, performance, and the use of artificial intelligence (AI) techniques. The research findings suggest diagnosticians in a clinical setting use dementia screening apps such as ALZ and CognitiveExams since they cover most of the domains for the diagnosis of neurocognitive disorders. Further, apps such as Cognity and ACE-Mobile have great potential as they use machine learning (ML) and AI techniques, thus improving the accuracy of the outcome and the efficiency of the screening process. Lastly, there was overlapping among the dementia screening apps in terms of activities and questions they contain therefore mapping these apps to the designated cognitive domains is a challenging task, which has been done in this research.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cognitive mapping; Dementia; MCI; Machine learning; Mobile apps; Neurodegenerative areas; Screening methods; Systematic review

Mesh:

Year:  2020        PMID: 32961306     DOI: 10.1016/j.jbi.2020.103573

Source DB:  PubMed          Journal:  J Biomed Inform        ISSN: 1532-0464            Impact factor:   6.317


  2 in total

1.  Checking the validity and reliability of the Japanese version of the Mini-Cog using a smartphone application.

Authors:  Yoshinobu Saito; Sho Nakamura; Ayumi Tanaka; Ryo Watanabe; Hiroto Narimatsu; Ung-Il Chung
Journal:  BMC Res Notes       Date:  2022-06-25

2.  DailyCog: A Real-World Functional Cognitive Mobile Application for Evaluating Mild Cognitive Impairment (MCI) in Parkinson's Disease.

Authors:  Sara Rosenblum; Ariella Richardson; Sonya Meyer; Tal Nevo; Maayan Sinai; Sharon Hassin-Baer
Journal:  Sensors (Basel)       Date:  2021-03-04       Impact factor: 3.576

  2 in total

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