Understanding the factors influencing acceptability of AI in medical imaging domains among healthcare professionals: A scoping review.

Journal: Artificial intelligence in medicine
Published Date: Nov 9, 2023

Abstract

BACKGROUND: Artificial intelligence (AI) technology has the potential to transform medical practice within the medical imaging industry and materially improve productivity and patient outcomes. However, low acceptability of AI as a digital healthcare intervention among medical professionals threatens to undermine user uptake levels, hinder meaningful and optimal value-added engagement, and ultimately prevent these promising benefits from being realised. Understanding the factors underpinning AI acceptability will be vital for medical institutions to pinpoint areas of deficiency and improvement within their AI implementation strategies. This scoping review aims to survey the literature to provide a comprehensive summary of the key factors influencing AI acceptability among healthcare professionals in medical imaging domains and the different approaches which have been taken to investigate them.

Authors

  • David Hua
    Department of Chemistry, University of Kansas, Lawrence, Kansas 66045, United States.
  • Neysa Petrina
    School of Computer Science, The University of Sydney, Australia.
  • Noel Young
    Sydney Medical School, The University of Sydney, Australia; Lumus Imaging, Australia.
  • Jin-Gun Cho
    Sydney Medical School, The University of Sydney, Australia; Western Sydney Local Health District, Australia; Lumus Imaging, Australia.
  • Simon K Poon
    School of Computer Science, The University of Sydney, Australia; Western Sydney Local Health District, Australia. Electronic address: simon.poon@sydney.edu.au.

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