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Radiologists' perceptions on AI integration: An in-depth survey study.

Maurizio Cè1, Simona Ibba2, Michaela Cellina3

  • 1Postgraduation School of Radiodiagnostic, University of Milan, via Festa del Perdono 7, 20122 Milan, Italy.

European Journal of Radiology
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PubMed
Summary

Radiologists show optimism towards artificial intelligence (AI) adoption in clinical practice, viewing it as an opportunity. However, concerns about AI literacy and practical efficacy require further attention for successful integration.

Keywords:
AIArtificial IntelligenceAutomatic detectionCADRadiologists perceptions

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Area of Science:

  • Radiology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Artificial intelligence (AI) is increasingly integrated into clinical practice.
  • Understanding radiologists' perceptions is crucial for effective AI adoption.

Purpose of the Study:

  • To assess radiologists' perceptions and attitudes regarding the adoption of AI in clinical practice.
  • To identify factors influencing AI acceptance and identify areas for improvement.

Main Methods:

  • A survey was conducted among radiologists from SIRM Lombardy.
  • Attitudes were assessed using a two-part questionnaire with Likert-type responses.
  • Exploratory data analysis and non-parametric tests were used for analysis.

Main Results:

  • 232 valid responses indicated generally optimistic outlooks on AI adoption.
  • While daily AI tool use was reported by 36.2%, only a third found AI decisive.
  • AI literacy gaps were noted, particularly among younger radiologists.
  • Radiologists perceived AI positively for detection and workload reduction but were skeptical about its role in decision-making and personalized medicine.
  • 61% viewed AI as an opportunity, 18% as a threat, and 84% emphasized the radiologist's essential role.

Conclusions:

  • Radiologists exhibit positive attitudes toward AI adoption, tempered by concerns about training and efficacy.
  • Addressing AI literacy gaps, especially in younger professionals, is vital.
  • Proactive adaptation to AI is crucial for maximizing its benefits in radiology.