Facing the AI challenge in radiology: Lessons learned from a regional survey among Austrian radiologists in academic and non-academic settings on perceptions and expectations towards artificial intelligence

Abstract

Aim: This study aimed to evaluate perceptions and expectations towards artificial intelligence (AI) applications in diagnostic radiology among radiologists across academic, non-academic and private practice settings in the Federal State of Styria, Austria. It also sought to determine how participant's characteristics and AI-specific knowledge might influence these views. Methods: An online quantitative survey comprising 20 multiple-choice questions in German language was distributed via email to radiologists in outpatient and hospital settings throughout Styria in 2024. Results: 0.01). However, opinions varied on AI's potential to outperform radiologists in diagnostics in the near future. There was no statistically significant relationship between participant's AI-specific knowledge and perceptions and expectations towards AI. Conclusion: The study reveals a generally positive attitude towards AI among radiologists, with uncertainties about its future performance compared to human radiologists. Although AI is anticipated to positively influence workload without reducing income, there may be a discrepancy between these expectations and actual outcomes.

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