痴呆
决策支持系统
计算机科学
医疗保健
临床决策支持系统
范围(计算机科学)
背景(考古学)
知识管理
数据科学
人工智能
管理科学
医学
工程类
政治学
程序设计语言
法学
古生物学
病理
疾病
生物
作者
Amirhossein Eslami Andargoli,Nalika Ulapane,Tuan Anh Nguyen,Muhammad Nadeem Shuakat,John Zelcer,Nilmini Wickramasinghe
标识
DOI:10.1016/j.artmed.2024.102815
摘要
In the context of dementia care, Artificial Intelligence (AI) powered clinical decision support systems have the potential to enhance diagnosis and management. However, the scope and challenges of applying these technologies remain unclear. This scoping review aims to investigate the current state of AI applications in the development of intelligent decision support systems for dementia care. We conducted a comprehensive scoping review of empirical studies that utilised AI-powered clinical decision support systems in dementia care. The results indicate that AI applications in dementia care primarily focus on diagnosis, with limited attention to other aspects outlined in the World Health Organization (WHO) Global Action Plan on the Public Health Response to Dementia 2017-2025 (GAPD). A trifecta of challenges, encompassing data availability, cost considerations, and AI algorithm performance, emerges as noteworthy barriers in adoption of AI applications in dementia care. To address these challenges and enhance AI reliability, we propose a novel approach: a digital twin-based patient journey model. Future research should address identified gaps in GAPD action areas, navigate data-related obstacles, and explore the implementation of digital twins. Additionally, it is imperative to emphasize that addressing trust and combating the stigma associated with AI in healthcare should be a central focus of future research directions.
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