Advances in computation pathology have continued at an impressive pace in recent years
[1]. New insights into digital pathology, combined with advances in artificial intelligence …

Deep Learning (DL) algorithms are a set of techniques that exploit large and/or complex real-
world datasets for cross-domain and cross-discipline prediction and classification tasks. DL …

Bioinformatics is a branch of science that refers to the management, acquisition,
manipulation, and presentation of complex biological data sets, while clinical informatics is …

The diagnosis of cancer is typically based on histopathological sections or biopsies on glass
slides. Artificial intelligence (AI) approaches have greatly enhanced our ability to extract …

This is a review on the use of artificial intelligence for digital breast pathology. A systematic
search on PubMed was conducted, identifying 17,324 research papers related to breast …

Breast cancer is the most common cancer and second leading cause of cancer-related
death worldwide. The mainstay of breast cancer workup is histopathological diagnosis …

Breast cancer, a high-incidence cancer among female, occupies a large incidence of total
female patients with cancer. Pathological examination is the gold standard for breast cancer …

Artificial Intelligence Applications in Human Pathology deals with the latest topics in
biomedical research and clinical cancer diagnostics. With chapters provided by true …

Pathology clinical practice has evolved by adopting technological advancements initially
regarded as potentially disruptive, such as electron microscopy, immunohistochemistry, and …

Breast cancer has the highest mortality rate. Therefore, histologic imaging evaluations must
detect breast cancer early. Traditional methods are time-consuming and limit pathologists' …