Background and Aims Manual histological assessment is currently the accepted standard for
diagnosing and monitoring disease progression in NASH, but is limited by variability in …

Artificial intelligence (AI) can extract complex information from visual data. Histopathology
images of gastrointestinal (GI) and liver cancer contain a very high amount of information …

The development of artificial intelligence (AI) has increased dramatically in the last 20 years,
with clinical applications progressively being explored for most of the medical specialties …

Background Clinical benefits of atezolizumab plus bevacizumab (atezolizumab–
bevacizumab) are observed only in a subset of patients with hepatocellular carcinoma and …

Background and aims Computed tomography (CT) scan is frequently used to detect
hepatocellular carcinoma (HCC) in routine clinical practice. The aim of this study is to …

Artificial intelligence (AI) is an umbrella term used to describe a cluster of interrelated fields.
Machine learning (ML) refers to a model that learns from past data to predict future data …

Tissue biomarkers are crucial for cancer diagnosis, prognosis assessment and treatment
planning. However, there are few known biomarkers that are robust enough to show true …

Abstract Originally proposed by John McCarthy in 1955, artificial intelligence (AI) has
achieved a breakthrough and revolutionized the processing methods of clinical medicine …

∙ The deep learning-based histopathology may serve as a promising tool to free the
pathologists from dull routine practice. to be related to somatic mutation burdens, 3, 4 which …

Background & Aims Patients with hepatocellular carcinoma (HCC) displaying
overexpression of immune gene signatures are likely to be more sensitive to …