Advancements in Cancer Research through Digital Pathology

This document is a collection of manuscripts, oral presentations, and posters related to advancements in cancer research using digital pathology. It presents various studies from 2021 to 2024 that focus on the application of artificial intelligence (AI) in cancer diagnostics and treatment. The manuscripts include topics such as the spatial mapping of immunosuppressive fibroblast gene signatures, AI-powered quantification of nuclear morphology, and comparisons of manual versus AI measurements of PD-L1 expression. Oral presentations discuss digital pathology-based biomarkers and AI assessments of pathologic responses to treatments. The posters highlight machine learning applications in predicting molecular subtypes, tumor microenvironment characteristics, and immune phenotypes. Overall, the document outlines significant contributions to the understanding of cancer through innovative digital pathology techniques and AI methodologies, emphasizing their potential impact on clinical outcomes and treatment strategies.