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

Ensuring diagnostic performance of artificial intelligence (AI) before introduction into clinical
practice is essential. Growing numbers of studies using AI for digital pathology have been …

A model's ability to express its own predictive uncertainty is an essential attribute for
maintaining clinical user confidence as computational biomarkers are deployed into real …

Artificial intelligence (AI) is a rapidly evolving field of computer science that involves the
development of computational programs that can mimic human intelligence. In particular …

Background Lung cancer has the highest mortality rate in the world, twice as high as the
second highest. On the other hand, pathologists are overworked and this is detrimental to …

Primary cutaneous lymphomas (CLs) represent a heterogeneous group of T-cell lymphomas
and B-cell lymphomas that present in the skin without evidence of extracutaneous …

Abstract Computational Pathology (CPath) is an interdisciplinary science that augments
developments of computational approaches to analyze and model medical histopathology …

Precise classification of histopathological images is crucial to computer-aided diagnosis in
clinical practice. Magnification-based learning networks have attracted considerable …

Simple Summary Histopathological examination of lymph node (LN) specimens allows the
detection of hematological diseases. The identification and the classification of lymphoma, a …

Simple Summary Papillary thyroid carcinoma is the most common type of thyroid cancer and
could be cured if diagnosed and treated early. In clinical practice, the primary method for …