Digital Pathology and AI: Whole-Slide Imaging, Cancer Classification, Biomarkers and Diagnostic Support

Melanocytic Neoplasm Differential Diagnosis with AI provides a practical framework for digital pathology, cancer diagnosis, and computational pathology, with attention to specimen quality and interpretation. Diagnostic context includes digital pathology, whole slide imaging, AI pathology, specimen handling, architecture, cytologic detail, and clinicopathologic correlation specific to this topic. Long-tail searches such as image analysis, cancer diagnosis, and computational pathology are addressed with attention to grading, staging, biomarkers, special stains, immunohistochemistry, or molecular testing when applicable. For pathology case 78, the emphasis remains on reproducible microscopic criteria, differential diagnosis, reporting language, and how tissue findings influence treatment planning. Careful interpretation also requires