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This article discusses the development and evaluation of an explainable AI model for diagnosing melanoma, as well as a reader study with clinicians to measure the impact of the AI on diagnostic accuracy, confidence, and trust. The study also addresses three types of errors that can occur in human-AI interactions and the importance of performance-based sub-group analysis in introducing AI into clinical practice.
