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Methodology for integrating artificial Intelligence in healthcare systems: learning from Covid-19 to prepare for Disease X

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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s43681-021-00111-x

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0001-5629-6857


Publisher:
Springer
Journal:
AI and Ethics More from this journal
Volume:
2
Pages:
623-630
Publication date:
2021-10-19
Acceptance date:
2021-10-06
DOI:
EISSN:
2730-5961


Language:
English
Keywords:
Pubs id:
1202889
Local pid:
pubs:1202889
Deposit date:
2021-10-14

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