Universität zu Köln

Huisman, Merel, Ranschaert, Erik, Parker, William, Mastrodicasa, Domenico ORCID: 0000-0001-8227-0757, Koci, Martin, Pinto de Santos, Daniel, Coppola, Francesca ORCID: 0000-0001-8957-4606, Morozov, Sergey, Zins, Marc, Bohyn, Cedric, Koc, Ural, Wu, Jie, Veean, Satyam, Fleischmann, Dominik, Leiner, Tim and Willemink, Martin J. (2021). An international survey on AI in radiology in 1,041 radiologists and radiology residents part 1: fear of replacement, knowledge, and attitude. Eur. Radiol., 31 (9). S. 7058 - 7067. NEW YORK: SPRINGER. ISSN 1432-1084

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Abstract

Objectives Radiologists' perception is likely to influence the adoption of artificial intelligence (AI) into clinical practice. We investigated knowledge and attitude towards AI by radiologists and residents in Europe and beyond. Methods Between April and July 2019, a survey on fear of replacement, knowledge, and attitude towards AI was accessible to radiologists and residents. The survey was distributed through several radiological societies, author networks, and social media. Independent predictors of fear of replacement and a positive attitude towards AI were assessed using multivariable logistic regression. Results The survey was completed by 1,041 respondents from 54 mostly European countries. Most respondents were male (n = 670, 65%), median age was 38 (24-74) years, n = 142 (35%) residents, and n = 471 (45%) worked in an academic center. Basic AI-specific knowledge was associated with fear (adjusted OR 1.56, 95% CI 1.10-2.21, p = 0.01), while intermediate AI-specific knowledge (adjusted OR 0.40, 95% CI 0.20-0.80, p = 0.01) or advanced AI-specific knowledge (adjusted OR 0.43, 95% CI 0.21-0.90, p = 0.03) was inversely associated with fear. A positive attitude towards AI was observed in 48% (n = 501) and was associated with only having heard of AI, intermediate (adjusted OR 11.65, 95% CI 4.25-31.92, p < 0.001), or advanced AI-specific knowledge (adjusted OR 17.65, 95% CI 6.16-50.54, p < 0.001). Conclusions Limited AI-specific knowledge levels among radiology residents and radiologists are associated with fear, while intermediate to advanced AI-specific knowledge levels are associated with a positive attitude towards AI. Additional training may therefore improve clinical adoption.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Huisman, Merel UNSPECIFIED UNSPECIFIED UNSPECIFIED Ranschaert, Erik UNSPECIFIED UNSPECIFIED UNSPECIFIED Parker, William UNSPECIFIED UNSPECIFIED UNSPECIFIED Mastrodicasa, Domenico UNSPECIFIED orcid.org/0000-0001-8227-0757 UNSPECIFIED Koci, Martin UNSPECIFIED UNSPECIFIED UNSPECIFIED Pinto de Santos, Daniel UNSPECIFIED UNSPECIFIED UNSPECIFIED Coppola, Francesca UNSPECIFIED orcid.org/0000-0001-8957-4606 UNSPECIFIED Morozov, Sergey UNSPECIFIED UNSPECIFIED UNSPECIFIED Zins, Marc UNSPECIFIED UNSPECIFIED UNSPECIFIED Bohyn, Cedric UNSPECIFIED UNSPECIFIED UNSPECIFIED Koc, Ural UNSPECIFIED UNSPECIFIED UNSPECIFIED Wu, Jie UNSPECIFIED UNSPECIFIED UNSPECIFIED Veean, Satyam UNSPECIFIED UNSPECIFIED UNSPECIFIED Fleischmann, Dominik UNSPECIFIED UNSPECIFIED UNSPECIFIED Leiner, Tim UNSPECIFIED UNSPECIFIED UNSPECIFIED Willemink, Martin J. UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-602220
DOI:	10.1007/s00330-021-07781-5
Journal or Publication Title:	Eur. Radiol.
Volume:	31
Number:	9
Page Range:	S. 7058 - 7067
Date:	2021
Publisher:	SPRINGER
Place of Publication:	NEW YORK
ISSN:	1432-1084
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language Radiology, Nuclear Medicine & Medical Imaging Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/60222