Deep learning-based models applied to digital pathology require large, curated datasets
with high-quality (HQ) annotations to perform correctly. In many cases, recruiting expert …

Objective The accuracy of artificial intelligence (AI) in medicine and in pathology in particular
has made major progress but little is known on how much these algorithms will influence …

Background: Generative artificial intelligence tools and applications (GenAI) are being
increasingly used in health care. Physicians, specialists, and other providers have started …

Digital pathology had a recent growth, stimulated by the implementation of digital whole
slide images (WSIs) in clinical practice, and the pathology field faces shortage of …

Objectives Esophageal cancer is a high occult malignant tumor. Even with good diagnosis
and treatment, the 5-year survival rate of esophageal cancer patients is still less than 30 …

Rapid progress has been made in artificial intelligence (AI) models for medical applications,
especially over the past 5 years, with substantial efforts focusing on diagnosis from medical …

Prostate cancer (PCa) is one of the deadliest cancers in men, and identifying cancerous
tissue patterns at an early stage can assist clinicians in timely treating the PCa spread. Many …

Since the introduction of the hematoxylin and eosin (H&E)-stained slide in 1876 as the
primary tool in the pathologist's toolbox up until the last decade, few tools, other than the …

Prostate cancer is one of the main diseases affecting men worldwide. The gold standard for
diagnosis and prognosis is the Gleason grading system. In this process, pathologists …

Abstract Machine learning technology is expected to support diagnosis and prognosis
prediction in medicine. We used machine learning to construct a new prognostic prediction …