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• W3205446535 abstract "Abstract 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." @default.
• W3205446535 created "2021-10-25" @default.
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• W3205446535 date "2021-10-19" @default.
• W3205446535 modified "2023-10-18" @default.
• W3205446535 title "Methodology for integrating artificial intelligence in healthcare systems: learning from COVID-19 to prepare for Disease X" @default.
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• W3205446535 doi "https://doi.org/10.1007/s43681-021-00111-x" @default.
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