Gastroenterology

Foundation model-enhanced unsupervised 3D deformable medical image registration.

Objective.Unsupervised deep learning has shown great promise in deformable image registration (DIR). These methods update model weights to optimize image similarity without requiring ground truth deformation vector fields (DVFs). However, they inherently face the ill-conditioning challenges due to structural ambiguities. This study aims to address these issues by integrating the implicit anatomica...

Machine Learning Model Predicts Recurrent Clostridioides difficile Infection in Patients With Inflammatory Bowel Disease (Recur CDI-IBD).

INTRODUCTION: Clostridioides difficile infection (CDI) present a significant challenge in patients with inflammatory bowel disease (IBD), with high recurrence rates and complications. Predicting recurrent CDI (rCDI) in IBD patients is crucial for implementing targeted interventions to improve patient outcomes. This study aimed to develop and validate a predictive model (RecurCDI-IBD) using supervi...

Real-Time Characterization of Colonic Polyps: A Multicenter Prospective Study Evaluating the CAD-EYE System in Screening Colonoscopies.

BACKGROUND AND STUDY AIMS: Polypectomy-related costs could potentially be reduced through optical diagnosis strategies, such as 'diagnose-and-leave' a...

STF: A Unified Framework for Joint Pixel-Level Segmentation and Tracking of Tissues in Endoscopic Surgery.

Endoscopic minimally invasive surgery relies on precise tissue video segmentation to avoid complications such as vascular bleeding or nerve injury. Ho...

Digital horizons: Exploring the future of AI-enabled gastroenterology in the Kingdom of Saudi Arabia.

Artificial intelligence is rapidly reshaping gastroenterology through demonstrable gains in diagnostic precision, procedural quality, and operational ...

Towards robust deep learning-based autosegmentation in MRI-planned gynecological brachytherapy: Importance of scalable development and comprehensive evaluation.

PURPOSE: To present comprehensive development and evaluation methodologies for a generalizable deep learning (DL)-driven autocontouring model of stand...

Identification of hypoxia- and mitophagy-related diagnostic biomarkers for ulcerative colitis based on bioinformatic analysis and machine learning.

BACKGROUND: Ulcerative colitis (UC) is a chronic nonspecific inflammatory bowel disease of unknown etiology that is associated with a significant risk...

Natural sources and bioactive mechanisms of anti-inflammatory peptides: from digestive metabolism to bioavailability enhancement strategies.

Anti-inflammatory peptides (AIPs), a class of biologically active molecules with high specificity and low toxicity, demonstrate outstanding potential ...

Machine Learning for Individual EV Classification Based on Highly Sensitive Multiplexed Mass Spectrometry Measurements.

Here, we report on combining Random Forest (RF) classification with nanoprojectile secondary ion mass spectrometry (NP-SIMS) to analyze single extrace...

[Diffusion cycle-consistent generative adversarial networks for pelvic active bone marrow segmentation].

OBJECTIVES: To establish a pelvic active bone marrow (ABM) segmentation method based on diffusion cycle-consistent generative adversarial networks for...

Pathomics Signature for Prognosis and CA19-9 Interception in Pancreatic Ductal Adenocarcinoma: A Real-Life, Multi-Center Study.

Histopathological hematoxylin and eosin (H&E) slides contain valuable prognostic information for pancreatic ductal adenocarcinoma (PDAC), yet systemat...

Lifespan Pancreas Morphology for Control Versus Type 2 Diabetes Using AI on Largescale Clinical Imaging.

Understanding how pancreas size and shape change with normal aging is critical for establishing a baseline to detect deviations in type 2 diabetes and...

An Artificial Intelligence-Guided Strategy to Reduce Poor Bowel Preparation: A Multicenter Randomized Controlled Study.

OBJECTIVES: Proper bowel preparation is crucial for increasing the adenoma detection rate. A novel application based on the use of a convolutional neu...

Interpretable Artificial Intelligence in Assisting Treatment Response Prediction for Locally Advanced Rectal Cancer After Neoadjuvant Chemoradiotherapy: A Prospective, Multicenter, Human-Model Interaction Study.

PURPOSE: Preoperative assessment of pathologic complete response (pCR) to neoadjuvant therapy is an urgent need for anorectal preservation in patients...

Improved visualization of pancreas and tumor boundaries using high-frequency kernels with deep-learning image reconstruction at high-strength level.

PURPOSE: This study aimed to investigate the feasibility of combining high-frequency reconstruction kernels and deep-learning image reconstruction at ...

MetaFX: feature extraction from whole-genome metagenomic sequencing data.

MOTIVATION: Microbial communities consist of thousands of microorganisms and viruses and have a tight connection with an environment, such as gut micr...

Clarifying the stopping rule and clinical value of AI-guided PEG titration for bowel preparation.

Unbiased clustering of acute-on-chronic liver failure patients using machine learning in a real-world ICU cohort.

Acute-on-chronic liver failure is a complex condition with varied definitions, complicating risk stratification and targeted management. We apply unsu...

Large-scale serum N-glycomics tracks N-glycosylation dynamics in hepatocellular carcinoma progression and enables early diagnosis.

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality, yet the role of N-glycosylation in its pathogenesis remains unclear. We applied...

Role of MRI radiomics in deep learning-based prediction of intestinal diseases.

BACKGROUND: Magnetic resonance imaging (MRI) is widely used for the diagnosis, evaluation, and follow-up of intestinal diseases. With advances in arti...