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This review synthesizes the current literature on explainable artificial intelligence and fairness in artificial intelligence applications for acute stroke management, identifies persistent challenges, and outlines recommendations for the development of equitable and trustworthy systems in stroke care.
Hospital physicians were more receptive for use of AI technologies in radiology compared to private practitioners, and practice patterns, economic factors, doctor-patient relationships, and frequency of interaction with the radiology department likely influence how AI use in radiology is perceived.
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