GERD

Triazolone-Functionalized Magnetic Nanoparticles for Hemoglobin Purification and Proteomics-Driven Biomarker Discovery in Diabetic Blood.

Hemoglobin, particularly glycated hemoglobin, serves as the gold standard for diagnosing diabetes in clinical settings. In this study, a triazolinone derivative, 3-chloromethyl-1,2,4-triazol-5-one (CMTO), was conjugated to polyethylenimide-modified magnetic nanoparticles via an amination reaction, resulting in the formation of a novel composite material, CMTO@FeO-NH. Molecular simulations revealed...

Deep learning-based evaluation of the severity of mitral regurgitation in canine myxomatous mitral valve disease patients using digital stethoscope recordings.

BACKGROUND: Myxomatous mitral valve disease (MMVD) represents the most prevalent cardiac disorder in dogs, frequently resulting in mitral regurgitation (MR) and congestive heart failure. Although echocardiography is the gold standard for diagnosis, it is an expensive tool that involves significant clinical training to ensure consistent application. Deep learning models offer an innovative approach...

Classification of image-enhanced endoscopy in colon tumors.

Colorectal cancer accounts for 10% of global cancer cases in each year, making accurate evaluation and resection crucial. Imaging-enhanced endoscopy h...

Integrated bioinformatics, machine learning, and molecular docking reveal crosstalk genes and potential drugs between periodontitis and systemic lupus erythematosus.

Evidence indicates a connection between periodontitis (PD) and systemic lupus erythematosus (SLE), though the underlying co-morbid mechanisms remain u...

Integrative bioinformatics and machine learning identify key crosstalk genes and immune interactions in head and neck cancer and Hodgkin lymphoma.

Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive malignancy with complex molecular underpinnings. Hodgkin lymphoma (HL), another d...

Improving Foundation Model for Endoscopy Video Analysis via Representation Learning on Long Sequences.

Recent advancements in endoscopy video analysis have relied on the utilization of relatively short video clips extracted from longer videos or million...

Evaluation of Artificial Intelligence Models for Nutritional Symptom Management in Breast Cancer Patients Undergoing Chemotherapy.

The purpose of the study is to determine if artificial intelligence (AI) models could provide dietary recommendations to manage chemotherapy-induced n...

GastroEndoNet: Comprehensive endoscopy image dataset for GERD and polyp detection.

The gastrointestinal (GI) system is fundamental to human health, supporting digestion, nutrient absorption, and waste elimination. Disruptions in GI f...

Deep Learning for Endoscopic Classification of Adenoid Hypertrophy.

OBJECTIVE: Endoscopy is a convenient and widely used method to evaluate adenoid size, but the subjectivity of its image diagnosis can result in over- ...

Protein interactions, network pharmacology, and machine learning work together to predict genes linked to mitochondrial dysfunction in hypertrophic cardiomyopathy.

This study looked at possible targets for hypertrophic cardiomyopathy (HCM), a condition marked by thickening of the ventricular wall, primarily in th...

The use of a convolutional neural network to automate radiologic scoring of computed tomography of paranasal sinuses.

BACKGROUND: Chronic rhinosinusitis (CRS) is diagnosed with symptoms and objective endoscopy or computed tomography (CT). The Lund-Mackay score (LMS) i...

Electrosurgical-laceration and stabilization of two PASCAL devices using artificial intelligence-based procedural planning: a case report.

BACKGROUND: Mitral transcatheter edge-to-edge repair (M-TEER) has been established as a treatment for severe mitral regurgitation (MR). However, recur...

Getting the best out of artificial intelligence in endoscopy.

Bioinformatics Approach to Identifying Molecular Targets of Isoliquiritigenin Affecting Chronic Obstructive Pulmonary Disease: A Machine Learning Pharmacology Study.

To identify the molecular targets and possible mechanisms of isoliquiritigenin (ISO) in affecting chronic obstructive pulmonary disease (COPD) by regu...

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

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 gastroenterology symposium, marking the first collaboration ...

Application of artificial intelligence in the diagnosis of malignant digestive tract tumors: focusing on opportunities and challenges in endoscopy and pathology.

BACKGROUND: Malignant digestive tract tumors are highly prevalent and fatal tumor types globally, often diagnosed at advanced stages due to atypical e...

Enhancing polyp classification: A comparative analysis of spatio-temporal techniques.

Colorectal cancer (CRC) is a major health concern, ranking as the third deadliest cancer globally. Early diagnosis of adenomatous polyps which are pre...

Early detection of esophageal cancer: Evaluating AI algorithms with multi-institutional narrowband and white-light imaging data.

Esophageal cancer is one of the most common cancers worldwide, especially esophageal squamous cell carcinoma, which is often diagnosed at a late stage...

Application of an Automated Deep Learning Program to A Diagnostic Classification Model: Differentiating High-Risk Adenomas Among Colorectal Polyps 10 mm or Smaller.

OBJECTIVE: This study aimed to develop a computer-aided diagnosis (CADx) model using an automated deep learning (DL) program to classify low- and high...