Advancements in computer vision and artificial intelligence (AI) carry the potential to make
significant contributions to health care, particularly in diagnostic specialties such as …

Applications of artificial intelligence and particularly deep learning to aid pathologists in
carrying out laborious and qualitative tasks in histopathologic image analysis have now …

To address the challenges posed by large-scale development, validation, and adoption of
artificial intelligence (AI) in pathology, we have constituted a consortium of academics, small …

Unlocking the full potential of pathology data by gaining computational access to histological
pixel data and metadata (digital pathology) is one of the key promises of computational …

Artificial intelligence (AI) has made impressive strides recently in interpreting complex
images, thanks to improvements in deep learning techniques and increasing computational …

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

Simple Summary The rapid development of technology has enabled numerous applications
of artificial intelligence (AI), especially in medical science. Histopathological assessment of …

Background and motivation Digital pathology has been evolving over the last years,
proposing significant workflow advantages that have fostered its adoption in professional …

Advances in digitizing tissue slides and the fast-paced progress in artificial intelligence,
including deep learning, have boosted the field of computational pathology. This field holds …

Recently, deep learning frameworks have rapidly become the main methodology for
analyzing medical images. Due to their powerful learning ability and advantages in dealing …