Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …

Background Deep learning is a state-of-the-art technology that has rapidly become the
method of choice for medical image analysis. Its fast and robust object detection …

The analysis of histopathology images with artificial intelligence aims to enable clinical
decision support systems and precision medicine. The success of such applications …

Computational pathology uses artificial intelligence to enable precision medicine and
decision support systems through the analysis of whole slide images. It has the potential to …

Renal cancer management is challenging from diagnosis to treatment and follow-up. In
cases of small renal masses and cystic lesions the differential diagnosis of benign or …

Context.—Prostate cancer diagnosis rests on accurate assessment of tissue by a
pathologist. The application of artificial intelligence (AI) to digitized whole slide images …

The field of anatomic pathology has been evolving in the last few decades and the
advancements have been largely fostered by innovative technology. Immunohistochemistry …

Background There is high demand to develop computer-assisted diagnostic tools to
evaluate prostate core needle biopsies (CNBs), but little clinical validation and a lack of …

Artificial intelligence (AI)‐based systems applied to histopathology whole‐slide images have
the potential to improve patient care through mitigation of challenges posed by diagnostic …

Artificial intelligence (AI) is the field of computer science that aims to build smart devices
performing tasks that currently require human intelligence. Through machine learning (ML) …