Gastroenterology

Analysis of B-Scan Ultrasonography Using Neural Networks to Predict Risk of Fibrosis in Patients With Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD).

OBJECTIVE: The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) continues to rise, underscoring the need for tools to stratify individual risk of disease progression. We evaluated whether logistic regression models augmented by deep learning-based predictions (DLPs) can improve the B-mode ultrasound-based identification of at-risk MASLD, defined as patients with incre...

Integrating Radiomics and Computational Pathology to Predict Early Recurrence of Pancreatic Ductal Adenocarcinoma and Uncover Its Biological Basis in Tumor Microenvironment.

BACKGROUND: Accurate prediction of early recurrence (ER) after radical resection remains a critical challenge in pancreatic ductal adenocarcinoma (PDAC). This study aimed to develop and validate an integrated radiomic-pathology (Rad-Path) model for ER prediction and to elucidate its underlying biological mechanisms. METHODS: A retrospective cohort of 225 PDAC patients who underwent R0 resection wa...

A Pt/Pd-Decorated SnO2-Based Electronic Nose for High-Precision Breath Analysis in Diagnosing SIBO.

Exhaled human breath contains disease-related biomarkers, enabling non-invasive medical diagnostics. Small intestinal bacterial overgrowth (SIBO) is t...

Interpretable prediction of occult lymph node metastasis in pancreatic ductal adenocarcinoma using a model fusing habitat radiomics and deep learning.

PURPOSE: To evaluate the value of integrating habitat radiomics features and deep learning features for predicting occult lymph node metastasis (OLNM)...

Robotic Pancreaticoduodenectomy with Right Lateral Approach to the Superior Mesenteric Artery: Surgical Artificial Intelligence-Based Visualization for Standardized Dissection.

BACKGROUND: Robotic pancreaticoduodenectomy enables precise vascular dissection, but dissection of the superior mesenteric artery (SMA) remains techni...

An Explainable Artificial Intelligence Tool (FibroX) for Detecting Advanced Liver Fibrosis in Type 2 Diabetes: Protocol for a Pilot Crossover Trial.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease is highly prevalent in adults with type 2 diabetes, and advanced fibrosis is its ...

Association of surgery with survival in small cell carcinoma of the digestive system: a population-based observational study using machine learning.

Identification of a novel platelet-related prognostic model for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a highly lethal malignancy with high invasiveness and metastasis. Despite progress in its treatment, the high mortal...

Interpretable machine learning and molecular simulations identify natural pancreatic lipase inhibitors and hydrophobic hotspot residues.

Pancreatic lipase (PL) is a validated peripheral target for limiting dietary fat absorption, yet structurally diverse natural inhibitors remain scarce...

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 u...

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 fe...

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...