Latest AI and machine learning research in gastroenterology for healthcare professionals.
Monocular depth and pose estimation play an important role in the development of colonoscopy-assiste...
Augmented reality can improve tumor localization in laparoscopic liver surgery. Existing registratio...
Computed Tomography (CT) is one of the most widely used and diagnostically information-dense imaging...
Artificial intelligence (AI) based segmentation has many medical applications but limited curated da...
Non-alcoholic fatty liver disease (NAFLD) is a globally prevalent hepatic condition caused by the bu...
The Updated Sydney System (USS) provides a standardized framework for grading gastritis and stratify...
Background: Large language models (LLMs) show promise for clinical decision support, yet most valida...
Endoscopy is essential in medical imaging, used for diagnosis, prognosis and treatment. Developing a...
Background: Pancreatic ductal adenocarcinoma is one of the most aggressive and lethal malignancies o...
Background and Objective The dysbiosis of human gut microbiome has been increasingly seen to have a ...
Background & Aims: Intrahepatic biliary epithelial cell (BEC) heterogeneity remains challenging to d...
Existing medical imaging datasets for abdominal CT often lack three-dimensional annotations, multi-o...
Fanconi anemia (FA) is a rare genetic disorder of impaired DNA repair characterized by progressive b...
Pancreatic ductal adenocarcinoma remains one of the most lethal malignancies, largely due to the abs...
Background: Liver cancer primarily develops in patients with chronic liver disease (CLD), yet most c...
Ductular Reactions (DRs) are dynamic and complex multicellular responses that occur as a result of v...
Purpose: Translating foundation models into clinical practice requires evaluating their performance ...
Liver fibrosis poses a substantial challenge in clinical practice, emphasizing the necessity for pre...
Urinary bladder cancer surveillance requires tracking tumor sites across repeated interventions, yet...
Purpose: Large language models (LLMs) are increasingly applied in radiology, but key challenges rema...
Target discovery for IBD has traditionally relied on genetic associations, which lack the cellular r...