Modern endoscopy relies on digital technology, from high-resolution imaging sensors and
displays to electronics connecting configurable illumination and actuation systems for …

Background Medical use cases for machine learning (ML) are growing exponentially. The
first hospitals are already using ML systems as decision support systems in their daily …

Artificial Intelligence (ai) systems are precious support for decision-making, with many
applications also in the medical domain. The interaction between mds and ai enjoys a …

Artificial Intelligence (AI) has made significant strides in revolutionizing cancer care,
encompassing various aspects from diagnosis to prevention and beyond. With its ability to …

AI-assisted screening and prevention programs have the potential to revolutionize disease
management and improve public health outcomes. By harnessing the power of artificial …

Colorectal polyps in the colon or rectum are precancerous growths that can lead to a more
severe disease called colorectal cancer. Accurate segmentation of polyps using medical …

Artificial intelligence, a computer-based concept that tries to mimic human thinking, is slowly
becoming part of the endoscopy lab. It has developed considerably since the first attempt at …

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

Background Endoscopic resection (ER) is widely applied to treat early colorectal cancer
(CRC). Predicting the invasion depth of early CRC is critical in determining treatment …

Irritable bowel syndrome (IBS) has a global prevalence of around 4.1% and is associated
with a low quality of life and increased healthcare costs. Current guidelines recommend that …