Impact of artificial intelligence on clinical radiography practice: Futuristic prospects in a low resource setting.

Journal: Radiography (London, England : 1995)
Published Date: Aug 13, 2021

Abstract

OBJECTIVES: Current trends in clinical radiography practice include the integration of artificial intelligence (AI) and related applications to improve patient care and enhance research. However, in low resource countries there are unique barriers to the process of AI integration. Using Ghana as a case study, this paper seeks to discuss the potential impact of AI on future radiographic practice in low-resource settings. The opportunities, challenges and the way forward to optimise the potential benefits of AI in future practice within these settings have been explored.

Authors

  • A-R Wuni
    Department of Imaging Technology and Sonography, School of Allied Health Sciences, College of Health and Allied Sciences, University of Cape Coast, Cape Coast, Ghana. Electronic address: abdul.razak.wuni@ucc.edu.gh.
  • B O Botwe
    Department of Radiography, School of Biomedical and Allied Health Sciences, College of Health Sciences, University of Ghana, Box KB143, Korle Bu, Accra, Ghana. Electronic address: sirbenard13@gmail.com.
  • T N Akudjedu
    Institute of Medical Imaging & Visualisation, Department of Medical Science & Public Health, Faculty of Health & Social Sciences, Bournemouth University, Bournemouth, UK. Electronic address: takudjedu@bournemouth.ac.uk.

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