人工智能在脆弱性识别和管理中的使用:一个范围审查协议
Sathya Karunananthan1,2, Arya Rahgozar3,4, Ramtin Hakimjavadi2,5
1Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada skarunan@uottawa.ca.
BMJ open
|December 28, 2023
概括
本范围审查将检查人工智能 (AI) 工具,用于识别和管理老年人的脆弱性. 目标是绘制临床虚弱护理中AI应用的当前证据.
科学领域:
- 老年学是指老年学的学科.
- 医疗信息学 医疗信息学
- 公共卫生 公共卫生
背景情况:
- 人口老龄化在识别和管理脆弱性方面带来了挑战.
- 人工智能 (AI) 为早期脆弱性检测和护理提供了潜在的解决方案.
- 复杂的脆弱表现使临床评估和管理变得复杂.
研究的目的:
- 对人工智能的开发和应用进行范围审查,包括机器学习和深度学习,用于脆弱性识别和管理.
- 确定临床工具,评估框架和与AI相关的评估结果.
- 探索知识用户参与AI开发和实施的脆弱性.
主要方法:
- 在八个主要的学术数据库 (Medline,Embase,PsycInfo,CINAHL,Ageline,Web of Science,Scopus,IEEE Xplore) 进行系统的搜索.
- 使用Arksey和O'Malley框架,由Levac等人增强. 和乔安娜·布里格斯研究所.
- 两个独立的审稿人将选标题,摘要和全文,然后进行数据图表和叙事综合.
主要成果:
- 本节不适用,因为摘要描述了审查的协议,而不是审查本身的结果.
结论:
- 本范围审查协议概述了一种综合方法,用于合成关于人工智能的证据,用于脆弱性护理.
- 调查结果将为医疗保健提供者,护理人员,患者和资助者提供有关AI在管理脆弱性方面的作用的信息.
- 传播包括同行评审的出版物,演讲和信息图表,以接触到各种利益相关者.
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