An update on computational pathology tools for genitourinary pathology practice: A review paper from the Genitourinary Pathology Society (GUPS)

An update on computational pathology tools for genitourinary pathology practice: A review paper from the Genitourinary Pathology Society (GUPS)

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Machine learning has been leveraged for image analysis applications throughout a multitude of subspecialties.This position paper provides a perspective on the evolutionary hp 15-ef1005ds trajectory of practical deep learning tools for genitourinary pathology through evaluating the most recent iterations of such algorithmic devices.Deep learning tools for genitourinary pathology demonstrate crimson tint dunks potential to enhance prognostic and predictive capacity for tumor assessment including grading, staging, and subtype identification, yet limitations in data availability, regulation, and standardization have stymied their implementation.