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Artificial intelligence (AI) is rapidly transforming numerous fields, and radiology stands at the forefront of this revolution [1]. AI-related research now dominates radiology publications, with every major journal issue featuring new algorithms promising improvements in lesion detection, segmentation, or classification. This enthusiasm is mirrored by growing clinical adoption: approximately 48% of European radiologists report using AI, mainly in computed tomography (CT) and magnetic resonance imaging (MRI) [2].
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Jayet et al. (2025) studied this question.
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