Gastroenterology

Unsupervised Single-Class Anomaly Detection in Rat Liver Using a Model of Normal Histomorphology.

An unsupervised, single-class anomaly detection approach based on a vision transformer architecture was developed to aid histopathology evaluation of rat liver from nonclinical toxicology studies. The approach was designed to detect any histopathology finding without requiring specific histopathology examples for training. The model was developed by training a vision transformer with approximately...

Evaluation of Computer-aided Detection for Identifying Missed Gastric Cancer After Endoscopic Submucosal Dissection.

OBJECTIVES: Computer-aided detection (CADe) using deep learning is promising for reducing missed gastric cancers (MGCs) and supporting physicians in double-checking endoscopic images. We aimed to evaluate the CADe efficacy for MGCs after endoscopic submucosal dissection (ESD). METHODS: We collected 2324 endoscopic images, including 60 of MGCs detected during surveillance esophagogastroduodenoscopy...

Radiomics Integrated with Deep Learning Based on Contrast-Enhanced MRI for Predicting Short-Term Efficacy of Drug-Eluting Beads Transarterial Chemoembolization in Hepatocellular Carcinoma from Multicenter Retrospective Study.

We aimed to develop and validate a predictive model combining radiomics, deep learning, and clinical features for the preoperative prediction of the s...

Evaluation of gastric cancer using artificial intelligence iterative reconstruction on abdominal CT: image quality and diagnostic accuracy.

PURPOSE: To investigate the clinical performance of a novel deep-learning based image reconstruction algorithm, namely artificial intelligence iterati...

Development and validation of a Bayesian network-based surgical risk-prediction tool for patients with small-bowel stricturing Crohn's disease.

BACKGROUND: Patients with small-bowel stricturing Crohn's disease (sbsCD) usually have a higher risk of intestinal surgical resection. We aimed to dev...

Antimony- and NSAID-Induced Hepatotoxicity at the Molecular Crossroads: Redox, Inflammasome and Programmed Cell-Death Networks as Therapeutic Targets for Natural Hepatoprotective Agents.

Drug- and metal-induced liver damage (DILI/MILI) continues to be a predominant cause of acute hepatic failure globally, with two clinically significan...

Deep Learning-Accelerated MRI Assessment of Hepatic Proton Density Fat Fraction: Agreement With Conventional Acquisition Across Manual and Automated Measurement Approaches.

BACKGROUND: Deep learning reconstruction can shorten breath-hold MRI for liver proton density fat fraction (DL-PDFF), but agreement with conventional ...

From Collapse to Active Self-Repair: Integrative Multi-Omics and Machine Learning Analysis Map the Hepatic Metabolic Adaption in Response to Simulated Spaceflight Stress.

Long-term spaceflight poses substantial challenges to human physiology, with the liver being highly susceptible due to its central metabolic role. To ...

CPTCs Drive Somatic-Visceral Communication via the Wnt Axis in Somatic Mechanotherapy: A Single-Cell Deep Learning Study.

Somatic mechanical stimulation (e.g., acupuncture) exerts systemic immunomodulatory effects, yet the cellular bridge translating peripheral physical f...

Comprehensive and reproducible grading of the Updated Sydney System in gastric biopsies using artificial intelligence: multi-pathologist validation and a reader study.

AIMS: The Updated Sydney System is the most widely used framework for histological grading of gastritis, but complete grading in routine gastric biops...

Transformer-Based Deep Learning Framework for Automated Lesion Detection in Capsule Endoscopy: A Comparative Study With CNN Architectures.

GOALS: To compare a vision transformer with 2 convolutional neural network architectures for multiclass lesion classification in capsule endoscopy ima...

Deep learning-based automated identification of papillary bladder cancer from endoscopic still images using SE-ResNeXt-50.

Bladder cancer remains a major global health challenge, necessitating rigorous endoscopic surveillance and the precise identification of neoplastic le...

Radiomics for Prediction of Microsatellite Instability Status in Gastric Cancer: A Systematic Review and Meta-Analysis.

BACKGROUND: Microsatellite instability (MSI) is a key biomarker for immunotherapy in gastric cancer (GC), but preoperative non-invasive prediction rem...

Creating Virtual Intraoperative CT Images From Endoscopic Video During Endoscopic Sinus Surgery: A Proof-of-Concept Study.

Artificial Intelligence in Liver Transplantation: A Systematic Review.

INTRODUCTION: Artificial intelligence (AI) is increasingly recognized as a transformative paradigm within transplantation medicine, offering advanced ...

An artificial intelligence-based endoscopic ultrasonography risk assessment and stratification for gastric stromal tumors.

BACKGROUND: Gastrointestinal stromal tumors (GISTs) are tumors with malignant potential. This research aims to develop an artificial intelligence (AI)...

Histological aging signatures for monitoring tissue-specific aging and disease.

Aging is the primary risk factor for chronic disease and is characterized by profound structural and architectural remodeling of human tissues. Here, ...

Hyperspectral Camera Imaging Tandem With HPLC-UV-ELSD Determination and Cell Bioassay for Geographical Discrimination and Quality Consistency Evaluation of Anoectochilus roxburghii.

INTRODUCTION: Anoectochilus roxburghii (AR) is a prized medicinal herb valued for its hepatoprotective effects. Its quality varies depending on geogra...

A novel adrenomedullin receptor signaling-based prognostic model predicts immunosuppressive microenvironment and informs therapeutic stratification in hepatocellular carcinoma: A retrospective bioinformatics study.

The adrenomedullin receptor signaling pathway plays a crucial role in tumor progression, yet its comprehensive implication in hepatocellular carcinoma...

Volatomic profiling of blood identifies environmental chemicals associated with metabolic dysfunction-associated steatotic liver disease in lean US adults.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects lean individuals, but the contribution of environmental exposures...