Given the recent success of artificial intelligence (AI) in computer vision applications, many
pathologists anticipate that AI will be able to assist them in a variety of digital pathology …

Abstract Machine learning is able to leverage large amounts of data to infer complex
patterns that are otherwise beyond the capabilities of rule-based systems and human …

The rapid development of artificial intelligence (AI) technologies in the context of the vast
amount of collectable data obtained from high-throughput sequencing has led to an …

The tumor-immune microenvironment (TIME) encompasses many heterogeneous cell types
that engage in extensive crosstalk among the cancer, immune, and stromal components …

Artificial intelligence (AI) solutions that automatically extract information from digital histology
images have shown great promise for improving pathological diagnosis. Prior to routine use …

Peptides comprise a versatile class of biomolecules that present a unique chemical space
with diverse physicochemical and structural properties. Some classes of peptides are able to …

Artificial intelligence (AI) digital health systems have drawn much attention over the last
decade. However, their implementation into medical practice occurs at a much slower pace …

Objectives Developing accurate supervised machine learning algorithms is hampered by
the lack of representative annotated datasets. Most data in anatomic pathology are …

In this chapter, we present a survey on various decision support methods that uses ontology
as its tool to provide the reasoning, medical knowledge list, attributes and relationship …

Programmed cell death protein-1 (PD-1) and its ligand (programmed death ligand 1, PD-L1)
inhibitors, as the rising stars of immunotherapy, have been widely used in clinical practice …