Gastroenterology

LQUnet: a vascular segmentation network based on multi-scale feature fusion and hierarchical self distillation.

Vessel segmentation has important clinical significance in medical image analysis, especially in the assessment of liver disease and preoperative planning for the accurate extraction of vascular structures puts forward higher requirements. To cope with the challenges of complex vascular morphology, diverse scales and easy loss of fine vessels, this paper proposes a novel vascular segmentation netw...

Medicinal and Edible Plants for the Management of Inflammatory Bowel Disease: Synergistic Modulation of the Microbiota-Metabolite-Immune Axis.

Inflammatory bowel disease (IBD) is a chronic condition driven by the intertwined interplay of gut dysbiosis, immune perturbation, and metabolic imbalance. Current single-target therapies often fail to durably restore homeostasis in this complex ecosystem, and have thereby increased interest in diet-based holistic interventions. Plants traditionally used as both food and medicine, such as Crataegu...

Identifying cathepsin B as a key regulator of programmed cell death in acute pancreatitis.

Acute pancreatitis (AP) lacks effective therapies, and excessive programmed cell death (PCD) drives its pathogenesis. This study identified cathepsin ...

Standardized scoring systems-essential for the AI Era in small-bowel capsule endoscopy.

Radiomics and artificial intelligence in pancreatic cyst characterization: future or fiction?

Pancreatic cystic lesions (PCLs) are increasingly detected due to the widespread use of cross-sectional imaging and represent a significant diagnostic...

Radiomics based on multiphasic contrast-enhanced CT combined with clinical features for differentiating hypovascular pancreatic neuroendocrine tumors and pancreatic ductal adenocarcinoma.

XGBoost-based model for predicting five-year survival in gastric cancer using clinical indicators.

Toward Precise Risk Stratification after the Functional Cure of Chronic Hepatitis B.

Chronic hepatitis B remains a major global health challenge despite the advances in antiviral therapy. Although hepatitis B surface antigen (HBsAg) se...

Artificial intelligence-based reclassification of gastric adenocarcinoma enables prognostic stratification via diffuse-type patch proportion.

BACKGROUND: Gastric adenocarcinoma (GAC) remains a major global health burden with marked heterogeneity, complicating diagnosis and prognostic assessm...

Delisting From Clinical Improvement in Liver Cirrhosis: A Machine Learning Decision Tree Analysis.

BACKGROUND: Following therapeutic advancements, recompensation has gained increasing recognition in patients on waitlist for liver transplantation (LT...

Machine learning-based identification of key genes underlying sex differences in hepatocellular carcinoma and targeted drug screening.

Hepatocellular carcinoma (HCC) shows a marked predominance in men, yet the molecular basis for this sex disparity remains unclear. The present study l...

Prediction of trajectories and outcomes in early-stage metabolic dysfunction-associated steatotic liver disease: a narrative review.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disorder, with manifestations ranging from steato...

Artificial Intelligence in Colonoscopy Surveillance for Lynch Syndrome: Emerging Evidence, Lessons Learned From Average-Risk Populations, and Future Directions.

Lynch syndrome (LS) is the most common hereditary colorectal cancer (CRC) syndrome and is characterized by an accelerated adenoma-carcinoma sequence, ...

Urinary Metabolomics and One-Class Classification To Discover Children Affected by Bile Acid Synthetic Disorders: A Case-Study.

Bile acid synthetic disorders (BASDs) are a group of rare metabolic disorders that involve the synthesis of bile acids. Symptoms often overlap with nu...

In Silico Prediction of Potential Bile Salt Export Pump Inhibitors Using Pharmacophore Models and Consensus Machine Learning.

The ATP-dependent bile salt export pump (BSEP) is a transporter responsible for moving bile salts from hepatocytes into bile canaliculi. Inhibition of...

Deep learning-based renal artery segmentation and angle estimation for registration of endoscopic images and 3D models in robot-assisted partial nephrectomy.

PURPOSE: Image-guided robot-assisted partial nephrectomy (RAPN) that incorporates three-dimensional (3D) models has improved both oncological and func...

Automated estimation of drain output in postoperative patients using deep learning on clinical images.

Postoperative drains are essential components of care in general surgery and intensive care units, where accurate monitoring of drain output is critic...

A novel risk stratification strategy for precision prevention of gastric cancer based on clinicopathological features and IGFBP7.

A time-series feature-based nomogram for the prediction of severe acute pancreatitis.

Integrating multi-omics data for enhanced prognosis prediction in gastric cancer post-neoadjuvant therapy.

BACKGROUND: Neoadjuvant therapy is crucial for locally advanced gastric cancer (LAGC), yet response varies significantly. Traditional models based on ...