Simple Summary Diagnosing cancer at an early stage increases the chance of performing
effective treatment in many tumour groups. Key approaches include screening patients who …

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

Context.—Prostate cancer diagnosis rests on accurate assessment of tissue by a
pathologist. The application of artificial intelligence (AI) to digitized whole slide images …

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

Complete digital pathology transformation for primary histopathological diagnosis is a
challenging yet rewarding endeavor. Its advantages are clear with more efficient workflows …

Pathology laboratories are increasingly using digital workflows. This has the potential of
increasing lab efficiency, but the digitization process also involves major challenges …

Imaging datasets in cancer research are growing exponentially in both quantity and
information density. These massive datasets may enable derivation of insights for cancer …

Digital pathology (DP) is being deployed in many pathology laboratories, but most reported
experiences refer to public health facilities. In this paper, we report our experience in DP …

Digital pathology workflows can improve pathology operations by allowing reliable and fast
retrieval of digital images, digitally reviewing pathology slides, enabling remote work and …

Objective There is increasing interest in using artificial intelligence (AI) in pathology to
improve accuracy and efficiency. Studies of clinicians' perceptions of AI have found only …