Gastroenterology

GERD

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

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A ubiquitous and interoperable deep learning model for automatic detection of pleomorphic gastroesophageal lesions.

In recent years, artificial intelligence (AI) has been widely explored to enhance capsule endoscopy ...

Identification of CXCR4 as a potential preventive gene in clear cell renal cell carcinoma from machine learning and immune analysis.

Clear cell renal cell carcinoma (ccRCC) represents a prevalent malignant kidney tumor characterized ...

Human protein interaction networks of ancestral and variant SARS-CoV-2 in organ-specific cells and bodily fluids.

Understanding SARS-CoV-2 human protein-protein interactions (PPIs) and the host response to infectio...

Artificial Intelligence in Gastrointestinal Endoscopy: The Japan Gastroenterological Endoscopy Society Position Statements.

Research and development of artificial intelligence (AI) in the field of gastrointestinal endoscopy ...

Aortic Stenosis and Mitral Regurgitation: Takeaways From the Heart Valve Collaboratory Workshop on Multivalvular Disease.

The management of multivalvular disease presents increasing challenges in clinical practice caused b...

Biomarker risk stratification with capsule sponge in the surveillance of Barrett's oesophagus: prospective evaluation of UK real-world implementation.

BACKGROUND: Endoscopic surveillance is the clinical standard for Barrett's oesophagus, but its effec...

The impact of artificial intelligence on the endoscopic assessment of inflammatory bowel disease-related neoplasia.

Inflammatory bowel disease (IBD) is a group of chronic inflammatory conditions of the gastrointestin...

A Systematic Review of the Clinical Impact of Implementing Artificial Intelligence in Upper Aerodigestive Tract Endoscopy.

BACKGROUND: Endoscopy is essential in upper aerodigestive tract (UADT) examination, particularly in ...

Recent advances in deep learning for protein-protein interaction: a review.

Deep learning, a cornerstone of artificial intelligence, is driving rapid advancements in computatio...

Advancing artificial intelligence applicability in endoscopy through source-agnostic camera signal extraction from endoscopic images.

INTRODUCTION: Successful application of artificial intelligence (AI) in endoscopy requires effective...

Identification of key proteins and pathways in myocardial infarction using machine learning approaches.

Acute myocardial infarction (AMI) is a leading cause of global morbidity and mortality, requiring de...

Immuno-transcriptomic analysis based on machine learning identifies immunity signature genes of chronic rhinosinusitis with nasal polyps.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a prevalent inflammatory disease where immunomo...

PCLT-PPI: Predicting Multi-type Interactions between Proteins based on Point Cloud Structure and Local Topology Preservation.

Protein-protein interactions (PPIs) play a crucial role in cellular biochemical reactions. Computati...

Artificial intelligence in endoscopy and colonoscopy: a comprehensive bibliometric analysis of global research trends.

BACKGROUND: Artificial intelligence (AI) has revolutionized the field of gastroenterology, particula...

Predicting the Compressive Properties of Carbon Foam Using Artificial Neural Networks.

This article focusses on predicting the compressive properties of polyurethane-derived carbon foam u...

AI-assisted multi-OMICS analysis reveals new markers for the prediction of AD.

Alzheimer's Disease (AD) is the most prevalent neurodegenerative disorder, characterized by progress...

Machine learning to predict de novo protein-protein interactions.

Advances in machine learning for structural biology have dramatically enhanced our capacity to predi...

Integrative machine learning and bioinformatics analysis unveil key genes for precise glioma classification and prognosis evaluation.

Gliomas exhibit significant heterogeneity and diverse molecular subtypes, and there are marked diffe...

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