European Radiology · 2021 · 231 citations · 14 references
MedicineMedical EducationRadiologyArtificial IntelligenceClinical Decision SupportDiagnostic RadiologyArtificial Intelligence AdoptionRadiological Risk AssessmentRadiology InformaticsRadiology Information SystemsAi Adoption IntentionAi Risk PerceptionLogistic RegressionMedian AgeMultivariable Regression AnalysisPerceived Artificial Intelligence RiskRadiology Artificial IntelligenceTechnology Acceptance Of Ai
Radiologists’ perception is likely to influence the adoption of artificial intelligence (AI) into clinical practice. The study aimed to assess radiologists’ and residents’ knowledge, attitudes, and fears regarding AI and to recommend integrating AI education into radiology curricula. A cross‑sectional survey was distributed via radiological societies, author networks, and social media to 1,041 radiologists and residents across 54 countries, and multivariable logistic regression identified predictors of fear and positive attitudes. Respondents with basic AI knowledge were more likely to fear replacement (OR 1.56), whereas intermediate or advanced knowledge reduced fear (OR 0.40–0.43) and was strongly linked to a positive attitude (OR 11.65–17.65), with 48% expressing a favorable view of AI.
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.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.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).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. • Intermediate and advanced AI-specific knowledge levels may enhance adoption of AI in clinical practice, while rudimentary knowledge levels appear to be inhibitive. • AI should be incorporated in radiology training curricula to help facilitate its clinical adoption.
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