Background Clinical medicine offers a promising arena for applying Machine Learning (ML)
models. However, despite numerous studies employing ML in medical data analysis, only a …

Abstract Background and Objectives In spite of rapid growth of artificial intelligence (AI) in
digestive endoscopy in lesion detection and characterization, the role of AI in inflammatory …

Colonoscopy is currently one of the most sensitive screening methods for colorectal cancer.
This study investigates the frontiers of intelligent colonoscopy techniques and their …

Foundation model, which is pre-trained on broad data and is able to adapt to a wide range
of tasks, is advancing healthcare. It promotes the development of healthcare artificial …

Endoscopic remission is an important therapeutic goal in ulcerative colitis (UC). The
Ulcerative Colitis Endoscopic Index of Severity (UCEIS) and Mayo Endoscopic Score (MES) …

Abstract The success of Large Vision Models (LVMs) is accompanied by vast data volumes,
which are prohibitively expensive in medical diagnosis. To address this, recent efforts exploit …

Background There has been an increase in the development of both machine learning (ML)
and deep learning (DL) prediction models in Inflammatory Bowel Disease. We aim in this …

The number of patients with inflammatory bowel disease (IBD) has been increasing. The
diagnosis is a difficult task for the gastroenterologist performing the endoscopic examination …

Assessing disease severity with ordinal classes, where each class reflects increasing
severity levels, benefits from loss functions designed for this ordinal structure. Traditional …

Video capsule endoscopy has transformed gastrointestinal endoscopy (GIE) diagnostics by
offering a non-invasive method for capturing detailed images of the gastrointestinal tract …