Gastroenterology

OCTN1 variants shape innate immunity and predict individual response to anti-TNFα in ulcerative colitis patients: An exploratory study.

BACKGROUND: Ulcerative colitis (UC) exhibits substantial heterogeneity in inflammatory pathways and therapeutic response. The organic cation transporter OCTN1 (SLC22A4) and its rs1050152 missense variant (L503F) have been implicated in innate immune activation and disease susceptibility. We investigated whether OCTN1 variants modulate monocyte inflammatory responses and predict clinical outcomes i...

Evaluation of AI-Driven Automatic Segmentation Algorithms for Lung Shunt Fraction Estimation in 90Y-Labeled Microsphere Therapy.

90Y-labeled microsphere (90Y-microsphere) hepatic arterial radioembolization is a direct treatment for hepatic neoplasms. Before therapy, the fraction of 90Y-microspheres that may shunt past the liver to the lungs, or lung shunt fraction (LSF), is estimated using 99mTc-macroaggregated albumin. LSF is commonly estimated using regions of interest around the lungs and liver on planar images, a method...

Next-generation AI for visually occult pancreatic cancer detection in a low-prevalence setting with longitudinal stability and multi-institutional generalisability.

BACKGROUND: Failure of conventional imaging to detect pancreatic ductal adenocarcinoma (PDA) at its visually occult pre-diagnostic stage is a primary ...

A machine learning predictive model for staging chronic hepatitis B inflammation based on non-invasive metrics.

Early screening and antiviral therapy for significant liver inflammation in chronic hepatitis B (CHB) remain significant barriers as the key to diseas...

Deep learning-based automatic scoring of drug-induced sleep endoscopy in obstructive sleep apnea.

Polysomnography is the standard tool for assessing obstructive sleep apnea (OSA) severity; however, it does not provide information regarding the anat...

Gastrointestinal endoscopic image style transfer using EndoStyle to improve artificial intelligence prediction models.

Artificial intelligence (AI) is increasingly used in gastrointestinal endoscopy for polyp detection and classification. However, most AI models are tr...

A multiobjective AI model for LNP engineering enhances tissue-selective mRNA delivery.

Lipid nanoparticle (LNP) delivery of RNA therapeutics is constrained by poor tissue selectivity and off-target toxicity. Most high-throughput screenin...

A novel system design for monocular laser assisted capsule endoscopy for 3D small bowel modeling.

The long, tortuous, and tissue-homogeneous structure of the small bowel makes image-based three-dimensional (3D) modeling studies technically complex....

Image quality improvement of liver ultrasound using unsupervised deep learning.

Chronic liver disease (CLD) and subsequent liver cirrhosis (LC) are common causes of death and healthcare-related socio-economical costs worldwide. Ul...

Gastric cancer susceptibility mapping using GIS and machine learning in East Azerbaijan province, Iran.

Machine Learning Prediction of Hospital Stay in Pediatric Typhoid Intestinal Perforation: Pilot Study.

INTRODUCTION: Typhoid intestinal perforation (TIP) remains a significant cause of pediatric morbidity in resource-limited settings, with prolonged hos...

Artificial Intelligence in Rhinology: A State-of-the-Art Review of Clinical Readiness and Implementation Pathways.

OBJECTIVE: To critically evaluate advances in artificial intelligence (AI) within rhinology, focusing on translational readiness, regulatory alignment...

The needle study: Machine learning as a new method for case-finding in celiac disease.

OBJECTIVES: Despite a well-defined diagnostic work-up, uncertainties persist regarding celiac disease (CeD) detection strategies in the general popula...

Machine Learning Models Using Hospital Admission Characteristics Do Not Optimally Predict Nosocomial Infection Development in a Global Cirrhosis Cohort.

BACKGROUND: Nosocomial infections (NI) in cirrhosis are associated with high mortality but could be preventable. Logistic regression (LR) models have ...

Automated Eosinophil Quantification Using Deep Learning to Predict Therapy Escalation in Pediatric Ulcerative Colitis.

BACKGROUND: Emerging evidence implicates eosinophils as important modulators of disease activity and therapeutic response in ulcerative colitis. Autom...

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 plan...

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 imbal...

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...