Which explainable AI methods in medical imaging are clinically impactful? A systematic literature review addressing the clinician's perspective

BackgroundExplainable Artificial Intelligence (XAI) has emerged as a strategy to enhance the transparency and interpretability of AI systems in medical imaging. Although numerous methods have been developed to generate explanations of model behavior, their evaluation has predominantly relied on technical performance metrics rather than clinician-centered assessment. The limited involvement of clinicians in the development and validation of XAI methods, together with the absence of clinically mea