Latest AI and machine learning research in gastroenterology for healthcare professionals.
RATIONALE AND OBJECTIVES: To investigate a computed tomography (CT)-based multiparameter deep learni...
Gastrointestinal cancer represents a significant health burden, necessitating innovative approaches ...
Disparities in access to the organ transplant waitlist are well-documented, but research into modifi...
BACKGROUND: Large language models may form the basis of clinical decision support tools to improve r...
BACKGROUND: Gastrointestinal bleeding is a serious adverse event of coronary artery bypass grafting ...
INTRODUCTION: Ogilvie's Syndrome (OS) is a rare but serious functional disorder characterized by dil...
BACKGROUND AND AIMS: Posthepatectomy liver failure (PHLF) remains a severe complication after hepate...
Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) is a major contributor to...
BACKGROUND: Despite technical advancements, minimally invasive liver surgery (MILS) for hepatocellul...
BACKGROUND: Laparoscopic repeat liver resection (LRLR) is still a challenging technique and requires...
INTRODUCTION: Large learning models (LLMs) such as GPT are advanced artificial intelligence (AI) mod...
To evaluate the clinical performance and safety of the ONIRY system for obstetric anal sphincter inj...
BACKGROUND: Over the years, various models, including both traditional and machine learning models, ...
BACKGROUND: Early complications increase in-hospital stay and mortality after intestinal obstruction...
BACKGROUND: Mild acute biliary pancreatitis (MABP) presents significant clinical and economic challe...
BACKGROUND: Current prediction models are suboptimal for determining mortality risk in patients with...
Programmed cell death (PCD) plays a critical role in cancer biology, influencing tumor progression a...
Drug-induced liver injury (DILI) toxicity is a condition when drugs have a destructive effect on the...
Gene selection is crucial for cancer classification using microarray data. In the interests of impro...
OBJECTIVE: The study aimed to develop machine learning (ML) models to predict the mortality of patie...
RATIONALE AND OBJECTIVES: This study constructed an interpretable machine learning model based on mu...