Radanliev Petar, De Roure David, Maple Carsten, Ani Uchenna
Department of Engineering Sciences, Oxford e-Research Centre, University of Oxford, Oxford, UK.
WMG Cyber Security Centre, University of Warwick, Coventry, UK.
AI Ethics. 2022;2(4):623-630. doi: 10.1007/s43681-021-00111-x. Epub 2021 Oct 19.
Artificial intelligence and edge devices have been used at an increased rate in managing the COVID-19 pandemic. In this article we review the lessons learned from COVID-19 to postulate possible solutions for a Disease X event. The overall purpose of the study and the research problems investigated is the integration of artificial intelligence function in digital healthcare systems. The basic design of the study includes a systematic state-of-the-art review, followed by an evaluation of different approaches to managing global pandemics. The study design then engages with constructing a new methodology for integrating algorithms in healthcare systems, followed by analysis of the new methodology and a discussion. Action research is applied to review existing state of the art, and a qualitative case study method is used to analyse the knowledge acquired from the COVID-19 pandemic. Major trends found as a result of the study derive from the synthesis of COVID-19 knowledge, presenting new insights in the form of a conceptual methodology-that includes six phases for managing a future Disease X event, resulting with a summary map of various problems, solutions and expected results from integrating functional AI in healthcare systems.
人工智能和边缘设备在管理新冠疫情方面的应用率不断提高。在本文中,我们回顾了从新冠疫情中吸取的经验教训,以推测针对X疾病事件的可能解决方案。该研究的总体目的和所调查的研究问题是将人工智能功能集成到数字医疗系统中。该研究的基本设计包括系统的最新技术综述,随后是对管理全球大流行的不同方法的评估。然后,研究设计致力于构建一种在医疗系统中集成算法的新方法,接着对新方法进行分析和讨论。采用行动研究来回顾现有技术水平,并使用定性案例研究方法来分析从新冠疫情中获得的知识。该研究的主要趋势源于对新冠疫情知识的综合,以概念方法的形式呈现了新的见解,该方法包括管理未来X疾病事件的六个阶段,并得出了将功能性人工智能集成到医疗系统中的各种问题、解决方案和预期结果的总结图。