Gastroenterology

The development of a prediction model based on deep learning for prognosis prediction of gastrointestinal stromal tumor: a SEER-based study.

Accurately predicting the prognosis of Gastrointestinal stromal tumor (GIST) patients is an importan...

Artificial intelligence to classify acquired intestinal injury in preterm neonates-a new perspective.

Enhancing Multi-species Liver Microsomal Stability Prediction through Artificial Intelligence.

Liver microsomal stability, a crucial aspect of metabolic stability, significantly impacts practical...

Enhancing gadoxetic acid-enhanced liver MRI: a synergistic approach with deep learning CAIPIRINHA-VIBE and optimized fat suppression techniques.

OBJECTIVE: To investigate whether a deep learning (DL) controlled aliasing in parallel imaging resul...

Improving Vessel Segmentation with Multi-Task Learning and Auxiliary Data Available Only During Model Training.

Liver vessel segmentation in magnetic resonance imaging data is important for the computational anal...

Deep learning-based multi-parametric magnetic resonance imaging (mp-MRI) nomogram for predicting Ki-67 expression in rectal cancer.

PURPOSE: To explore the value of deep learning-based multi-parametric magnetic resonance imaging (mp...

Non-invasive assessment of response to transcatheter arterial chemoembolization for hepatocellular carcinoma with the deep neural networks-based radiomics nomogram.

BACKGROUND: Transcatheter arterial chemoembolization (TACE) is a mainstay treatment for intermediate...

Comparison of an interpretable extreme gradient boosting model and an artificial neural network model for prediction of severe acute pancreatitis.

INTRODUCTION: Acute pancreatitis (AP) that progresses to persistent organ failure is referred to as ...

Early and accurate diagnosis of steatotic liver by artificial intelligence (AI)-supported ultrasonography.

OBJECTIVES: Steatotic liver disease is the most frequent chronic liver disease worldwide. Ultrasonog...

OrgaSegment: deep-learning based organoid segmentation to quantify CFTR dependent fluid secretion.

Epithelial ion and fluid transport studies in patient-derived organoids (PDOs) are increasingly bein...

MIS-Net: A deep learning-based multi-class segmentation model for CT images.

The accuracy of traditional CT image segmentation algorithms is hindered by issues such as low contr...

Deep learning algorithm for the automated detection and classification of nasal cavity mass in nasal endoscopic images.

Nasal endoscopy is routinely performed to distinguish the pathological types of masses. There is a l...

Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery: a systematic review and meta-analysis.

BACKGROUND: Machine learning (ML) approaches have become increasingly popular in predicting surgical...

Automatic segmentation of hepatocellular carcinoma on dynamic contrast-enhanced MRI based on deep learning.

. Precise hepatocellular carcinoma (HCC) detection is crucial for clinical management. While studies...

Pediatric endoscopy: how can we improve patient outcomes and ensure best practices?

INTRODUCTION: Strategies to promote high-quality endoscopy in children require consensus around pedi...

[Reduction of Motion Artifacts in Liver MRI Using Deep Learning with High-pass Filtering].

PURPOSE: To investigate whether deep learning with high-pass filtering can be used to effectively re...

Robot-assisted gastric endoscopic submucosal dissection significantly improves procedure time at challenging dissection locations.

BACKGROUND: Endoscopic submucosal dissection (ESD) is the standard treatment for early malignant sto...

Enabling large-scale screening of Barrett's esophagus using weakly supervised deep learning in histopathology.

Timely detection of Barrett's esophagus, the pre-malignant condition of esophageal adenocarcinoma, c...

Digital pathology with artificial intelligence analysis provides insight to the efficacy of anti-fibrotic compounds in human 3D MASH model.

Metabolic dysfunction-associated steatohepatitis (MASH) is a severe liver disease characterized by l...

Enhancing site selection strategies in clinical trial recruitment using real-world data modeling.

Slow patient enrollment or failing to enroll the required number of patients is a disruptor of clini...

Artificial Intelligence-assisted colonoscopy and colorectal cancer screening: Where are we going?

Colorectal cancer is a significant global health concern, necessitating effective screening strategi...