The integration of AI into digital pathology has the potential to transform cancer diagnostics by enabling scalable, quantitative analysis of tissue specimens. However, widespread deployment of AI-assisted pathology remains challenged by the need for costly imaging infrastructure and the lack of reliable mechanisms to assess prediction confidence.
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