Digital histopathological images, high‐resolution images of stained tissue samples, are a
vital tool for clinicians to diagnose and stage cancers. The visual analysis of patient state …

Histopathology images; microscopy images of stained tissue biopsies contain fundamental
prognostic information that forms the foundation of pathological analysis and diagnostic …

Aims Artificial intelligence (AI) provides a powerful tool to extract information from digitised
histopathology whole slide images. During the last 5 years, academic and commercial …

Abstract Machine learning techniques have great potential to improve medical diagnostics,
offering ways to improve accuracy, reproducibility and speed, and to ease workloads for …

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

Recent advances in artificial intelligence show tremendous promise to improve the
accuracy, reproducibility, and availability of medical diagnostics across a number of medical …

Histopathology plays a fundamental role in the diagnosis and subtyping of solid tumors and
has become a cornerstone of modern precision oncology. Histopathological evaluation is …

Histopathological images contain rich phenotypic information that can be used to monitor
underlying mechanisms contributing to disease progression and patient survival outcomes …

Deep learning algorithms have shown benefits for pathology in the context of risk
stratification of tumors. Although the results are promising, several steps have to be made to …

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