Abstract Large Language Models are forms of artificial intelligence that use deep learning
algorithms to decipher large amounts of text and exhibit strong capabilities like question …

Computational pathology refers to applying deep learning techniques and algorithms to
analyse and interpret histopathology images. Advances in artificial intelligence (AI) have led …

Digital pathology has transformed the traditional pathology practice of analyzing tissue
under a microscope into a computer vision workflow. Whole slide imaging allows …

Abstract Computational Pathology (CPath) is an interdisciplinary science that augments
developments of computational approaches to analyze and model medical histopathology …

This paper discusses some overlooked challenges faced when working with machine
learning models for histopathology and presents a novel opportunity to support “Learning …

Digital pathology, powered by whole-slide imaging technology, has the potential to
transform the landscape of cancer research and diagnosis. By converting traditional …

Pathology laboratories are undergoing digital transformations, adopting innovative
technologies to enhance patient care. Digital pathology systems impact clinical, education …

Cytopathology represents a well established diagnostic approach because of its limited cost,
reliability, and minimal invasiveness with respect to other methodologies. The evolving …

Both pathology and cytopathology still rely on recognizing microscopical morphologic
features, and image analysis plays a crucial role, enabling the identification, categorization …

The Banff Digital Pathology Working Group (DPWG) was established with the goal to
establish a digital pathology repository; develop, validate, and share models for image …