For decades, it has been postulated that digital pathology is the future. By now it is safe to say that we are living that future. Digital pathology has expanded into all aspects of pathology, including human diagnostic pathology, veterinary diagnostics, research, drug development, regulatory toxicologic pathology primary reads, and peer review. Digital tissue image analysis has enabled users to extract quantitative and complex data from digitized whole-slide images. The following editorial provides an overview of the content of this special issue of Toxicologic Pathology to highlight the range of key topics that are included in this compilation. In addition, the editors provide a commentary on important current aspects to consider in this space, such as accessibility of publication content to the machine learning-novice pathologist, the importance of adequate test set selection, and allowing for data reproducibility.
Keywords: artificial intelligence; digital pathology; machine learning; tissue image analysis.