Traditional pathology approaches have played an integral role in the delivery of diagnosis,
semi-quantitative or qualitative assessment of protein expression, and classification of …

In modern clinical practice, digital pathology has a crucial role and is increasingly a
technological requirement in the scientific laboratory environment. The advent of whole-slide …

Malignant mesothelioma (MM) is an aggressive cancer primarily diagnosed on the basis of
histological criteria. The 2015 World Health Organization classification subdivides …

This paper reviews state-of-the-art research solutions across the spectrum of medical
imaging informatics, discusses clinical translation, and provides future directions for …

The key pathological hallmarks—extracellular plaques and intracellular neurofibrillary
tangles (NFT)—described by Alois Alzheimer in his seminal 1907 article are still central to …

In this white paper, experts from the Digital Pathology Association (DPA) define terminology
and concepts in the emerging field of computational pathology, with a focus on its …

Deep learning methods for digital pathology analysis are an effective way to address
multiple clinical questions, from diagnosis to prediction of treatment outcomes. These …

Context.—Controversies and uncertainty persist in prostate cancer grading. Objective.—To
update grading recommendations. Data Sources.—Critical review of the literature along with …

Artificial intelligence (AI) and machine learning have significantly influenced many facets of
the healthcare sector. Advancement in technology has paved the way for analysis of big …

Digital pathology (DP) is being increasingly employed in cancer diagnostics, providing
additional tools for faster, higher-quality, accurate diagnosis. The practice of diagnostic …