Among 230 randomized subjects in 8 centers, the adenoma miss rate (AMR) was 15.5%
when CADe was used in the first colonoscopy, and 32.4% when colonoscopy without CADe …

Although this excitement remains somewhat speculative, AI-assisted polyp detection (CADe)
is an area that has reached a degree of maturation in terms of the level of clinical evidence …

Quality improvement in colorectal cancer screening and surveillance by colonoscopy is
based on the assumption that an increase in adenoma detection rate (ADR) has the …

The performance of artificial intelligence-aided colonoscopy (AIAC) in a real-world setting
has not been described. We compared adenoma and polyp detection rates (ADR/PDR) in a …

Screening colonoscopy could effectively lower colorectal cancer (CRC) risk and lead to a
considerable financial burden. Artificial intelligence (AI), specifically computer-aided …

Background: Artificial intelligence (AI) could minimize the operator-dependent variation in
colonoscopy quality. Computer-aided detection (CADe) has improved adenoma detection …

Once a novel feature of science fiction, in recent years artificial intelligence (AI) has
pervaded our everyday lives. Facial recognition to access our phones, self-driving or self …

Background We have developed the computer-aided detection (CADe) system using an
original deep learning algorithm based on a convolutional neural network for assisting …

While research on machine learning and artificial intelligence (AI) applications for polyp
detection in colonoscopy have existed since at least the early 1990s (1), there has been a …

Background and study aims Adenoma detection rate (ADR) is a well-accepted quality
indicator of screening colonoscopy. In recent years, the added value of artificial intelligence …