Gastroenterology

Towards transparent and interpretable screening: multi-biofluid FTIR spectroscopy with LLM-Augmented explainability for pancreatic cancer detection.

Early detection of pancreatic cancer remains a critical challenge in oncology, with current diagnostic methods often failing to identify the disease until advanced stages. However, diagnostic accuracy alone may be insufficient for clinical adoption as regulatory frameworks and clinical workflows increasingly demand transparent, interpretable AI systems. This study investigates Fourier Transform In...

Trusted polyp segmentation via multi-scale evidence ensemble in colonoscopy images.

PURPOSE: Accurate and reliable polyp segmentation is essential for early colorectal cancer detection. Although recent methods employing multi-scale feature aggregation have achieved high accuracy, their reliability in challenging clinical scenarios remains insufficient. Existing uncertainty-aware approaches primarily estimate uncertainty only at the decision layer, failing to exploit multi-scale t...

Relationships between periodontitis and inflammatory bowel disease: Screening and functional analysis of endoplasmic reticulum stress-related biomarkers.

This study aimed to explore the relationship between periodontitis (PD) and inflammatory bowel disease (IBD), focusing on changes in the expression of...

Action classification for endoscopic pituitary adenoma resection: a consensus-based study.

PURPOSE: Pituitary adenoma resection via the endoscopic transsphenoidal approach is technically demanding, with outcomes influenced by surgical skill....

Phase-constrained zero-shot self-supervised learning for BLADE liver MRI reconstruction.

INTRODUCTION: Liver MRI plays a critical role in the diagnosis and monitoring of liver disease; however, image quality is often degraded by respirator...

Intraindividual comparison of 3-T and 5-T gadoxetic acid-enhanced MRI for evaluating HCC: initial findings.

BACKGROUND: We aimed to evaluate the utility of 5-T Gadolinium-ethoxybenzyl diethylenetriaminepentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonan...

Towards a neuro-symbolic approach for precision anti-reflux surgery.

Deepath-SCC: a deep learning model for accurate tissue origin identification in squamous cell carcinoma.

Squamous cell carcinoma (SCC) is a common malignancy that arises in diverse organs and often exhibits overlapping histological and immunophenotypic fe...

Artificial intelligence augmented imaging of pancreatic fluid collections in acute pancreatitis.

Acute pancreatitis (AP) is a significant global health burden, with pancreatic fluid collections (PFCs) posing major diagnostic and therapeutic challe...

Deep learning-based pathomics signature predicts prognosis and treatment response in gastric cancer: a multicenter retrospective study.

The existing TNM staging system provides insufficient prognostic information in gastric cancer (GC) patients. This study aims to establish a pathomics...

Predicted meta-omics: A potential solution to multi-omics data scarcity in microbiome studies.

Imbalances in the gut microbiome have been linked to conditions such as inflammatory bowel disease, diabetes, and cancer. While metagenomics and ampli...

High-Throughput Screening for Ageing and Age-Related Disease Drug Discovery: Advances and Challenges.

Ageing is the primary risk factor for many chronic, degenerative, and life-threatening disorders, yet the translational pipeline for geroprotective in...

An Interpretable Model Combining Brain Imaging and Clinical Indicators for Predicting Overt Hepatic Encephalopathy.

BACKGROUND: Differentiating overt hepatic encephalopathy (OHE) from covert hepatic encephalopathy (CHE) remains challenging due to overlapping symptom...

Efferocytosis-related biomarkers and immune infiltration in pancreatic ductal adenocarcinoma based on single-cell sequencing and machine learning: a comprehensive bioinformatics analysis and experimental validation.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly invasive and lethal malignancy, with its complex tumor microenvironment (TME) severely...

Artificial intelligence for metabolic dysfunction-associated steatotic liver disease diagnosis: A systematic review.

Metabolic dysfunction-associated steatotic liver disease (MASLD) poses significant diagnostic challenges. We conducted a systematic review of artifici...

The Impact of Specific Prompt Engineering Techniques on the Readability of LLM-Generated Patient Materials in Gastroenterology and Hepatology.

BACKGROUND AND AIMS: Health literacy significantly impacts patient outcomes. While the average American reads at an 8th grade reading level, healthcar...

FedLiverNet: a federated learning framework for privacy-preserving and efficient liver cancer detection.

Liver cancer continues to be a significant health issue on the global front, and proper segmentation of the liver and the tumor formed from the comput...

Volatomics-based biomarkers for non-invasive diagnosis and monitoring of inflammatory bowel disease.

BACKGROUND: Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, is a chronic disorder that markedly impairs quality of...

Intraoperative video-based artificial intelligence model exceeding surgeon accuracy for predicting severe fibrosis in minimally invasive liver surgery.

Accurate evaluation of liver fibrosis is essential for surgical planning in patients with hepatocellular carcinoma (HCC), as advanced fibrosis or cirr...

Federated CT foundation models for multi-center detection of lymph node metastasis in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with prognosis strongly influenced by the presence of lymph node ...