Endocuff With or Without Artificial Intelligence-Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial.

Introduction: Both artificial intelligence (AI) and distal attachment devices have been shown to improve adenoma detection rate and reduce miss rate during colonoscopy. We studied the combined effect of Endocuff and AI on enhancing detection rates of various colonic lesions.

Methods: This was a 3-arm prospective randomized colonoscopy study involving patients aged 40 years or older.

Blue-light imaging or narrow-band imaging for proximal colonic lesions: a prospective randomized tandem colonoscopy study.

Background And Aims: Blue-light imaging (BLI) is a new image-enhanced endoscopy with a wavelength filter similar to narrow-band imaging (NBI). We compared the 2 with white-light imaging (WLI) on proximal colonic lesion detection and miss rates.

Methods: In this 3-arm prospective randomized study with tandem examination of the proximal colon, we enrolled patients aged ≥40 years.

Machine learning models in the prediction of 1-year mortality in patients with advanced hepatocellular cancer on immunotherapy: a proof-of-concept study.

Introduction: Immunotherapy is a new promising treatment for patients with advanced hepatocellular carcinoma (HCC), but is costly and potentially associated with considerable side effects. This study aimed to evaluate the role of machine learning (ML) models in predicting the 1-year cancer-related mortality in advanced HCC patients treated with immunotherapy.

Method: 395 HCC patients who had received immunotherapy (including nivolumab, pembrolizumab or ipilimumab) between 2014 and 2019 in Hong Kong were included.

Feasibility study of a single-use balloon-assisted robotic colonoscope in healthy volunteers.

Despite its widespread adoption, colonoscope still has its limitations. Advancement is often limited by the looping of colon. The isolation of SARS-CoV-2 in stool raises concern for the risk of disease transmission.