TY - JOUR
T1 - Attitudes Toward Artificial Intelligence Among Radiologists, IT Specialists, and Industry
AU - Jungmann, Florian
AU - Jorg, Tobias
AU - Hahn, Felix
AU - Pinto dos Santos, Daniel
AU - Jungmann, Stefanie Maria
AU - Düber, Christoph
AU - Mildenberger, Peter
AU - Kloeckner, Roman
N1 - Publisher Copyright:
© 2020 The Association of University Radiologists
PY - 2021/6
Y1 - 2021/6
N2 - Objectives: We investigated the attitudes of radiologists, information technology (IT) specialists, and industry representatives on artificial intelligence (AI) and its future impact on radiological work. Materials and Methods: 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. Results: 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). Conclusion: 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.
AB - Objectives: We investigated the attitudes of radiologists, information technology (IT) specialists, and industry representatives on artificial intelligence (AI) and its future impact on radiological work. Materials and Methods: 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. Results: 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). Conclusion: 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.
UR - http://www.scopus.com/inward/record.url?scp=85085072186&partnerID=8YFLogxK
U2 - 10.1016/j.acra.2020.04.011
DO - 10.1016/j.acra.2020.04.011
M3 - Journal articles
C2 - 32414637
AN - SCOPUS:85085072186
SN - 1076-6332
VL - 28
SP - 834
EP - 840
JO - Academic Radiology
JF - Academic Radiology
IS - 6
ER -