Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …

In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …

Abstract Vision Transformers (ViTs) and their multi-scale and hierarchical variations have
been successful at capturing image representations but their use has been generally …

Artificial intelligence (AI) has shown promise for diagnosing prostate cancer in biopsies.
However, results have been limited to individual studies, lacking validation in multinational …

Quantitative evaluation of tissue images is crucial for computational pathology (CPath) tasks,
requiring the objective characterization of histopathological entities from whole-slide images …

The successful use of artificial intelligence (AI) for diagnostic purposes has prompted the
application of AI-based cancer imaging analysis to address other, more complex, clinical …

Multiple instance learning (MIL) has been increasingly used in the classification of
histopathology whole slide images (WSIs). However, MIL approaches for this specific …

A large-scale and well-annotated dataset is a key factor for the success of deep learning in
medical image analysis. However, assembling such large annotations is very challenging …

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

Traditional pathology approaches have played an integral role in the delivery of diagnosis,
semi-quantitative or qualitative assessment of protein expression, and classification of …