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使用移动应用程序进行痴呆症医学筛查:一项系统评价及新的映射模型。

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

机构信息

Digital Technologies, Manukau Institute of Technology, Auckland, New Zealand.

Department of Psychology, University of Huddersfield, Huddersfield, UK.

出版信息

J Biomed Inform. 2020 Nov;111:103573. doi: 10.1016/j.jbi.2020.103573. Epub 2020 Sep 20.

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.

摘要

早期发现是成功应对痴呆症的关键,痴呆症是老年人常见的神经认知疾病。因此,使用移动应用程序(app)等技术平台进行筛查可能为加快诊断过程和提高可及性提供重要机会。由于缺乏基于移动应用程序的痴呆症和轻度认知障碍(MCI)诊断和筛查工具的研究,本系统评价旨在根据特定的纳入和排除标准,确定现有的基于移动的痴呆症和轻度认知障碍(MCI)应用程序。更重要的是,我们从全面性、有效性、性能以及人工智能(AI)技术的使用等方面对这些工具进行了批判性分析。研究结果表明,临床诊断医生可以使用 ALZ 和 CognitiveExams 等痴呆症筛查应用程序,因为它们涵盖了神经认知障碍诊断的大部分领域。此外,Cognity 和 ACE-Mobile 等应用程序具有很大的潜力,因为它们使用机器学习(ML)和 AI 技术,从而提高了结果的准确性和筛查过程的效率。最后,痴呆症筛查应用程序在包含的活动和问题方面存在重叠,因此将这些应用程序映射到指定的认知领域是一项具有挑战性的任务,本研究对此进行了探索。

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