Latest AI and machine learning research in gastroenterology for healthcare professionals.
PURPOSE: Automated surgical instrument segmentation is a prerequisite for AI-assisted guidance in endoscopic spine surgery. Deployment-realistic comparisons of foundation-model and conventional deep learning architectures - accounting for the detector dependency of bbox-prompted models - remain lacking. METHODS: Seven deep learning pipelines were evaluated for binary instrument segmentation: U-Net...
Gastrointestinal nematodes (GIN) are a major health concern in dogs, particularly in high-density environments such as shelters. Toxocara canis, Ancylostoma spp., and Trichuris vulpis are widely distributed, with recognised veterinary and zoonotic relevance. Effective prevention requires improved understanding of environmental and management-related risk factors driving transmission. This study in...
INTRODUCTION: The scarcity of donor organs necessitates the development of refined prognostic tools to optimize candidate selection and survival outco...
To determine lactate metabolism-associated biomarkers for non-alcoholic fatty liver disease (NAFLD). Based on NAFLD datasets from the gene expression ...
For locally advanced rectal cancer (LARC), neoadjuvant chemoradiotherapy (nCRT) combined with total mesorectal excision has emerged as the standard th...
Accurate preoperative differentiation of gastric cancer T4a/b stages is crucial for surgical planning and prognosis. However, conventional CT assessme...
OBJECTIVE: Postoperative metachronous liver metastasis (MLM) in colorectal cancer (CRC) patients is often difficult to predict using conventional clin...
BACKGROUND: Precise surgical procedures are critical to improving the survival outcomes for colon cancer patients. Currently, there is no dedicated in...
While gasdermin (GSDM)-mediated pyroptosis is a potent immune effector, its antiviral potential remains largely untapped. Here, we introduce viral pro...
BACKGROUND: Accurate staging of liver fibrosis is crucial for risk stratification in patients with metabolic dysfunction-associated steatotic liver di...
BACKGROUND: This study focuses on exploring the co-morbid mechanisms by which Bisphenol A (BPA) induces non-alcoholic fatty liver disease (NAFLD) and ...
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies worldwide, and accurate prognostic prediction remains highly challengin...
Hepatocellular carcinoma (HCC) exhibits substantial interpatient heterogeneity, leading to markedly variable outcomes and survival even among patients...
Hepatotoxicity represents a major adverse outcome of chemical exposure, as the liver plays a central role in xenobiotic metabolism and detoxification....
BACKGROUND: Large language models (LLMs) have shown promising performance in medical knowledge assessment; however, their capacity to assist real-worl...
BACKGROUND AND STUDY AIM: Identifying high-risk patients for recurrence after endoscopic resection (ER) of T1 colorectal cancer (CRC) remains challeng...
OBJECTIVE: Ultrasound fusion imaging is a hybrid technique that combines real-time ultrasonography (US) with pre-acquired computed tomography (CT) or ...
Coumarins are a group of naturally occurring compounds that have garnered significant interest for their potential anticancer properties, characterize...
OBJECTIVES: Metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) weakened the ...
BACKGROUND: Graph-based machine learning approaches, including Knowledge Graph Embedding (KGE) methods and Graph Neural Networks (GNNs), have emerged ...