Gastroenterology

Latest AI and machine learning research in gastroenterology for healthcare professionals.

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Direct-acting antivirals (DAA) positively affect depression and cognitive function in patients with chronic hepatitis C.

The aim of the study was to determine how depression and cognitive dysfunction in patients with chro...

Characterization of Enterocytozoon hepatopenaei infection stages in shrimp using machine learning and gene network analysis.

Enterocytozoon hepatopenaei (EHP), causing hepatopancreatic microsporidiosis (HPM), significantly im...

Development of Multiparametric Prognostic Models for Stereotactic Magnetic Resonance Guided Radiation Therapy of Pancreatic Cancers.

PURPOSE: Stereotactic magnetic resonance guided adaptive radiation therapy (SMART) is a new option f...

Deep learning-based reconstruction and superresolution for MR-guided thermal ablation of malignant liver lesions.

OBJECTIVE: This study evaluates the impact of deep learning-enhanced T1-weighted VIBE sequences (DL-...

An ensemble learning model to predict lymph node metastasis in early gastric cancer.

Lymph node metastasis is a critical factor for determining therapeutic strategies and assessing the ...

Enlightened prognosis: Hepatitis prediction with an explainable machine learning approach.

Hepatitis is a widespread inflammatory condition of the liver, presenting a formidable global health...

Automated Whole-Liver Fat Quantification with Magnetic Resonance Imaging-Derived Proton Density Fat Fraction Map: A Prospective Study in Taiwan.

BACKGROUND/AIMS: Magnetic resonance imaging (MRI) with a proton density fat fraction (PDFF) sequence...

Generation of surgical reports for lymph node dissection during laparoscopic gastric cancer surgery based on artificial intelligence.

PURPOSE: This study aimed to develop an artificial intelligence (AI) model for the surgical report o...

GONNMDA: A Ordered Message Passing GNN Approach for miRNA-Disease Association Prediction.

Small non-coding molecules known as microRNAs (miRNAs) play a critical role in disease diagnosis, tr...

Integrating single-cell RNA sequencing, WGCNA, and machine learning to identify key biomarkers in hepatocellular carcinoma.

The microarray and single-cell RNA-sequencing (scRNA-seq) datasets of hepatocellular carcinoma (HCC)...

Machine Learning-Guided Fluid Resuscitation for Acute Pancreatitis Improves Outcomes.

INTRODUCTION: Ariel Dynamic Acute Pancreatitis Tracker (ADAPT) is an artificial intelligence tool us...

Fully robotic recipient left graft living donor liver transplantation.

We report the first 2 cases of fully robotic recipient left graft living donor liver transplants, de...

Artificial intelligence for intraoperative video analysis in robotic-assisted esophagectomy.

BACKGROUND: Robotic-assisted minimally invasive esophagectomy (RAMIE) is a complex surgical procedur...

A Novel Natural Language Processing Tool Improves Colonoscopy Auditing of Adenoma and Serrated Polyp Detection Rates.

BACKGROUND AND STUDY AIMS: Determining adenoma detection rate (ADR) and serrated polyp detection rat...

The reality of modeling irritable bowel syndrome: progress and challenges.

INTRODUCTION: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is often the...

Gd-EOB-DTPA-enhanced MRI radiomics and deep learning models to predict microvascular invasion in hepatocellular carcinoma: a multicenter study.

BACKGROUND: Microvascular invasion (MVI) is an important risk factor for early postoperative recurre...

Machine learning models for pancreatic cancer diagnosis based on microbiome markers from serum extracellular vesicles.

Pancreatic cancer (PC) is a fatal disease with an extremely low 5-year survival rate, mainly because...

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