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Attitudes Toward Artificial Intelligence Among Radiologists, IT Specialists, and Industry.

Authors
  • Jungmann, Florian1
  • Jorg, Tobias2
  • Hahn, Felix2
  • Pinto Dos Santos, Daniel3
  • Jungmann, Stefanie Maria4
  • Düber, Christoph2
  • Mildenberger, Peter2
  • Kloeckner, Roman2
  • 1 Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Germany. Electronic address: [email protected] , (Germany)
  • 2 Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Germany. , (Germany)
  • 3 Department of Radiology, University Hospital of Cologne, Germany. , (Germany)
  • 4 Psychological Institute, Johannes Gutenberg University of Mainz, Germany. , (Germany)
Type
Published Article
Journal
Academic radiology
Publication Date
Jun 01, 2021
Volume
28
Issue
6
Pages
834–840
Identifiers
DOI: 10.1016/j.acra.2020.04.011
PMID: 32414637
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

We investigated the attitudes of radiologists, information technology (IT) specialists, and industry representatives on artificial intelligence (AI) and its future impact on radiological work. During a national meeting for AI, eHealth, and IT infrastructure in 2019, we conducted a survey to obtain participants' attitudes. A total of 123 participants completed 28 items exploring AI usage in medicine. The Kruskal-Wallis test was used to identify differences between radiologists, IT specialists, and industry representatives. The strongest agreement between all respondents occurred with the following: plausibility checks are important to understand the decisions of the AI (93% agreement), validation of AI algorithms is mandatory (91%), and medicine becomes more efficient in the age of AI (86%). In contrast, only 25% of the respondents had confidence in the AI results, and only 17% believed that medicine will become more human through the use of AI. The answers were significantly different between the three professions for four items: relevance for protocol selection in cross-sectional imaging (p = 0.034), medical societies should be involved in validation (p = 0.028), patients should be informed about the use of AI (p = 0.047), and AI should be part of medical education (p = 0.026). Currently, a discrepancy exists between high expectations for the future role of AI and low confidence in the results. This attitude was similar across all three groups. The demand for plausibility checks and the need to prove the usefulness in randomized controlled studies indicate what is needed in future research. Copyright © 2020 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

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