Clinicians and software developers need to understand how proposed machine learning
(ML) models could improve patient care. No single metric captures all the desirable …

Artificial intelligence (AI) has the potential to assist in endoscopy and improve decision
making, particularly in situations where humans may make inconsistent judgments. The …

Methods Our Colonoscopy Quality Assurance Program database reflects comprehensive
audits based on standardized clinical documentation. 1–4 We monitor preparation quality …

Colonoscopy is the gold standard for early diagnosis and pre-emptive treatment of colorectal
cancer by detecting and removing colonic polyps. Deep learning approaches to polyp …

The field of artificial intelligence is rapidly evolving, and there has been an interest in its use
to predict the risk of lymph node metastasis in T1 colorectal cancer. Accurately predicting …

Background and aims Seattle protocol biopsies for Barrett's Esophagus (BE) surveillance
are labour intensive with low compliance. Dysplasia detection rates vary, leading to missed …

Artificial intelligence (AI) has shown promising results in digestive endoscopy, especially in
capsule endoscopy (CE). However, some physicians still have some difficulties and fear the …

The use of artificial intelligence (AI) in clinical support systems is increasing. In this article,
we focus on AI support for continuous interaction scenarios. A thorough understanding of …

Background: Artificial intelligence (AI) is rapidly infiltrating multiple areas in medicine, with
gastrointestinal endoscopy paving the way in both research and clinical applications …

Objectives There is uncertainty regarding the efficacy of artificial intelligence (AI) software to
detect advanced subtle neoplasia, particularly flat lesions and sessile serrated lesions …