Recent developments in deep learning have enabled data-driven algorithms that can reach
human-level performance and beyond. The development and deployment of medical image …

Colorectal cancer (CRC) is the third most common cancer worldwide, with the highest
incidence reported in high-income countries. However, because of the slow progression of …

Background and Aims Recently, the use of computer-aided detection (CADe) for
colonoscopy has been investigated to improve the adenoma detection rate (ADR). We …

Background/Aims The real-world effectiveness of computer-aided detection (CADe) systems
during colonoscopies remains uncertain. We assessed the effectiveness of the novel CADe …

Artificial intelli-gence (AI) is expected to assist us by mimicking the process of human
learning. The hope is that AI will significantly improve our GI-practice from image …

Background Computer-aided detection (CADe) of colorectal polyps has been shown to
increase adenoma detection rates, which would potentially shorten subsequent surveillance …

Background: Artificial intelligence (AI) has significantly impacted medical imaging,
particularly in gastrointestinal endoscopy. Computer-aided detection and diagnosis systems …

BACKGROUND The presence of premalignant polyps on colonoscopy is an indicator of
metachronous colorectal cancer. Looping during colonoscopy is associated with old age …

Colorectal cancer is a significant global health concern, necessitating effective screening
strategies to reduce its incidence and mortality rates. Colonoscopy plays a crucial role in the …

Artificial Intelligence (AI) will radically transform digestive endoscopy in the next decade. The
assistance of computer-vision algorithms has very high performance in pattern recognition of …