Clinical routine in hepatology involves the diagnosis and treatment of a wide spectrum of
metabolic, infectious, autoimmune and neoplastic diseases. Clinicians integrate qualitative …

Precision oncology relies on the identification of targetable molecular alterations in tumor
tissues. In many tumor types, a limited set of molecular tests is currently part of standard …

Artificial intelligence (AI) can predict the presence of molecular alterations directly from
routine histopathology slides. However, training robust AI systems requires large datasets …

Artificial Intelligence (AI) can support diagnostic workflows in oncology by aiding diagnosis
and providing biomarkers directly from routine pathology slides. However, AI applications …

Artificial intelligence (AI) has a multitude of applications in cancer research and oncology.
However, the training of AI systems is impeded by the limited availability of large datasets …

Deep learning methods have emerged as powerful tools for analyzing histopathological
images, but current methods are often specialized for specific domains and software …

Colorectal cancer (CRC) is a primary global health concern, and identifying the molecular
pathways, genetic subtypes, and mutations associated with CRC is crucial for precision …

The interpretation of digitized histopathology images has been transformed thanks to
artificial intelligence (AI). End-to-end AI algorithms can infer high-level features directly from …

Artificial intelligence (AI)-based techniques are increasingly being explored as an emerging
ancillary technique for improving accuracy and reproducibility of histopathological …

Current approaches for classification of whole slide images (WSI) in digital pathology
predominantly utilize a two-stage learning pipeline. The first stage identifies areas of interest …