Gastroenterology

Automated machine learning for early prediction of systemic inflammatory response syndrome in acute pancreatitis.

BACKGROUND: Systemic inflammatory response syndrome (SIRS) is a frequent and serious complication of...

Prediction of Tumor Budding Grading in Rectal Cancer Using a Multiparametric MRI Radiomics Combined with a 3D Vision Transformer Deep Learning Approach.

RATIONALE AND OBJECTIVES: The objective is to assess the effectiveness of a multiparametric MRI radi...

Deep Visual Proteomics maps proteotoxicity in a genetic liver disease.

Protein misfolding diseases, including α1-antitrypsin deficiency (AATD), pose substantial health cha...

An interpretable framework for gastric cancer classification using multi-channel attention mechanisms and transfer learning approach on histopathology images.

The importance of gastric cancer (GC) and the role of deep learning techniques in categorizing GC hi...

An application of deep learning model InceptionTime to predict nausea, vomiting, diarrhoea, and constipation using the gastro-intestinal pacemaker activity drug database (GIPADD).

The accurate preclinical prediction of adverse drug reactions (ADRs), such as nausea and vomiting, r...

Gut microbiome research: Revealing the pathological mechanisms and treatment strategies of type 2 diabetes.

The high prevalence and disability rate of type 2 diabetes (T2D) caused a huge social burden to the ...

Development and application of deep learning-based diagnostics for pathologic diagnosis of gastric endoscopic submucosal dissection specimens.

BACKGROUND: Accurate diagnosis of ESD specimens is crucial for managing early gastric cancer. Identi...

Transformer-based skeletal muscle deep-learning model for survival prediction in gastric cancer patients after curative resection.

BACKGROUND: We developed and evaluated a skeletal muscle deep-learning (SMDL) model using skeletal m...

Self-supervised network predicting neoadjuvant chemoradiotherapy response to locally advanced rectal cancer patients.

Radiographic imaging is a non-invasive technique of considerable importance for evaluating tumor tre...

Can artificial intelligence help to reduce intraprocedural bleedings during third-space endoscopy?

Biophysical modeling and artificial intelligence for quantitative assessment of anastomotic blood supply in laparoscopic low anterior rectal resection.

PURPOSE: Fluorescence imaging is critical for intraoperative intestinal perfusion assessment in colo...

Machine learning-based disease risk stratification and prediction of metabolic dysfunction-associated fatty liver disease using vibration-controlled transient elastography: Result from NHANES 2021-2023.

BACKGROUND: Metabolic dysfunction-associated fatty liver disease (MAFLD) is a common chronic liver d...

Comparative study of XGBoost and logistic regression for predicting sarcopenia in postsurgical gastric cancer patients.

The use of machine learning (ML) techniques, particularly XGBoost and logistic regression, to predic...

EFCNet enhances the efficiency of segmenting clinically significant small medical objects.

Efficient segmentation of small hyperreflective dots, key biomarkers for diseases like macular edema...

A retrospective study using machine learning to develop predictive model to identify rotavirus-associated acute gastroenteritis in children.

BACKGROUND: Rotavirus is the leading cause of severe dehydrating diarrhea in children under 5 years ...

Comment on "Optimized machine learning model for predicting unplanned reoperation after rectal cancer anterior resection".

Uncertainty-aware segmentation quality prediction via deep learning Bayesian Modeling: Comprehensive evaluation and interpretation on skin cancer and liver segmentation.

Image segmentation is a critical step in computational biomedical image analysis, typically evaluate...

MRI radiomics combined with delta-radiomics model for predicting pathological complete response in locally advanced rectal cancer patients after neoadjuvant chemoradiotherapy: A multi-institutional study.

PURPOSE: To construct and validate a magnetic resonance imaging (MRI) radiomics combined with delta-...

RCPE in association with the American College of Gastroenterology and the Scottish Society of Gastroenterology - Gastroenterology: A global perspective.

On 6 November 2024, the Royal College of Physicians of Edinburgh (RCPE) hosted its annual gastroente...

Integrated multi-omics analysis and machine learning refine molecular subtypes and clinical outcome for hepatocellular carcinoma.

The high morbidity and mortality of hepatocellular carcinoma (HCC) impose a substantial economic bur...

AI-enabled opportunistic measurement of liver steatosis in coronary artery calcium scans predicts cardiovascular events and all-cause mortality: an AI-CVD study within the Multi-Ethnic Study of Atherosclerosis (MESA).

INTRODUCTION: About one-third of adults in the USA have some grade of hepatic steatosis. Coronary ar...