IMPORTANCE Histopathological diagnoses of tumors from tissue biopsy after hematoxylin and eosin (H&E) dye staining is the criterion standard for oncological care, but H&E staining requires trained operators, dyes and reagents, and precious tissue samples that cannot be reused. OBJECTIVES To use deep learning algorithms to develop models that perform accurate computational H&E staining of native nonstained prostate core biopsy images and to develop methods for interpretation of H&E staining deep learning models and analysis of computationally stained images by computer vision and clinical approaches. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study used hundreds of thousands of native nonstained RGB (red, green, and blue channel) whole slide image (WSI) patches of prostate core tissue biopsies obtained from excess tissue material from prostate core biopsies performed in

About one fifth of apparent false negative diagnoses for HGUC can be because of overdiagnosis of HGUC by surgical pathologists. If poor preservation or obscured samples are called nondiagnostic, the sensitivity/specificity of UC for HGUC can be as high as 94%/71%. Diagn. Cytopathol. 2016;44:994-999. © 2016 Wiley Periodicals, Inc.

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