Gastroenterology

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 mas...

[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 cy...

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 pan...

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 ba...

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 a...

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 ...

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 ...

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 str...

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-glycosylati...

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 follo...

Deep-learning pipeline for automated skeletal muscle segmentation and sarcopenia detection.

BACKGROUND: Sarcopenia, characterized by progressive skeletal muscle loss, is associated with poor o...

Machine learning-based risk modeling for safety-focused learning curve assessment in robotic left-sided colorectal cancer surgery.

The transition from laparoscopic to robotic surgery for left-sided colorectal cancer raises safety c...

Hybrid imaging-clinical model for predicting microvascular invasion in hepatocellular carcinoma using deep learning-derived features from CT.

The role of adipose tissue in predicting microvascular invasion (MVI) in patients with hepatocellula...

Development and Validation of a Urinary Exosomal miRNA Diagnostic Panel for Early Detection of Esophageal Cancer.

Esophageal squamous cell carcinoma (ESCC) remains a leading cause of cancer-related mortality, with ...

Multiparametric MRI radiomics nomogram predicts synchronous distant metastasis in rectal cancer.

This study aimed to evaluate the utility of a multiparametric MRI-based radiomics nomogram for ident...

Semi-Supervised Fatty Liver Classification Using Attention-Based Graph Neural Network Models.

BACKGROUND: Fatty liver disease is a common condition linked to metabolic syndrome, cardiovascular d...

Artificial intelligence in gastrointestinal endoscopy: a global clinical trial analysis.

Interpretable machine learning model for predicting in-hospital mortality in elderly acute pancreatitis: Development and validation in a multicenter cohort.

BACKGROUND: Elderly acute pancreatitis (AP) patients face significantly higher in-hospital all-cause...

Development and validation of an interpretable machine learning model for non-invasive screening of precancerous gastric lesions using symptom and lifestyle data: a multicentre cohort study.

BACKGROUND: Precancerous gastric lesions (PLGC) are a critical stage in gastric cancer progression, ...

Morphological characterization of a novel model of steatohepatitis in the FAH-/- pig.

Metabolic dysfunction-associated steatohepatitis (MASH) is a global health care burden. Appropriate ...

A prognostic signature of ferroptosis and lipid metabolism related genes predicts survival and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a common and aggressive form of cancer. There is an in...