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

Auto-brewery syndrome (ABS), also called gut fermentation syndrome, is an extremely
infrequent but also underrecognized disorder where ethanol is produced endogenously …

Self-supervised learning (SSL) has been successful in building patch embeddings of small
histology images (eg 224 x 224 pixels) but scaling these models to learn slide embeddings …

Drug-induced liver injury (DILI) presents significant diagnostic challenges, and recently
artificial intelligence-based deep learning technology has been used to predict various …

Deep learning has recently become one of the most popular methods of image analysis. In
non-clinical studies, several tissue slides are generated to investigate the toxicity of a test …

Artificial intelligence (AI)-based analysis has recently been adopted in the examination of
histological slides via the digitization of glass slides using a digital scanner. In this study, we …

Pathology, a cornerstone of medical diagnostics and research, is undergoing a revolutionary
transformation fueled by digital technology, molecular biology advancements, and big data …

A system for analysis of histopathology data within a pharmaceutical R&D environment has
been developed with the intention of enabling interdisciplinary collaboration. State-of-the-art …

Machine learning (ML) in toxicological sciences is growing exponentially, which presents
unprecedented opportunities and brings up important considerations for using ML in this …

In nonclinical toxicity studies, stage-aware evaluation is often expected to assess drug-
induced testicular toxicity. Although stage-aware evaluation does not require identification of …