Peptic Ulcer Disease

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 ch...

CASCADE-FSL: Few-shot learning for collateral evaluation in ischemic stroke.

Assessing collateral circulation is essential in determining the best treatment for ischemic stroke ...

Prediction of moderate to severe bleeding risk in pediatric immune thrombocytopenia using machine learning.

UNLABELLED: This study aimed to develop and validate a risk prediction model for moderate to severe ...

Utilisation of Deep Neural Networks for Estimation of Cajal Cells in the Anal Canal Wall of Patients with Advanced Haemorrhoidal Disease Treated by LigaSure Surgery.

Interstitial cells of Cajal (ICCs) play a key role in gastrointestinal smooth muscle contractions, b...

Preoperative Factors Associated With In-Hospital Major Bleeding After Percutaneous Coronary Intervention: A Systematic Review.

BACKGROUND: Preoperative risk assessment of bleeding after percutaneous coronary intervention (PCI) ...

Identification of biomarkers associated with M1 macrophages in the ST-segment elevation myocardial infarction through bioinformatics and machine learning approaches.

ST-segment elevation myocardial infarction (STEMI) is considered a critical cardiac condition with a...

A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images.

Deep learning has significantly contributed to medical imaging and computer-aided diagnosis (CAD), p...

Predicting protein-protein interaction with interpretable bilinear attention network.

BACKGROUND AND OBJECTIVE: Protein-protein interactions (PPIs) play the key roles in myriad biologica...

Natural language processing for identifying major bleeding risk in hospitalised medical patients.

BACKGROUND: Major bleeding is a severe complication in critically ill medical patients, resulting in...

Exploring new drug treatment targets for immune related bone diseases using a multi omics joint analysis strategy.

In the field of treatment and prevention of immune-related bone diseases, significant challenges per...

Development and validation of a machine learning model to predict hemostatic intervention in patients with acute upper gastrointestinal bleeding.

BACKGROUND: Acute upper gastrointestinal bleeding (UGIB) is common in clinical practice and has a wi...

Development of an artificial intelligence-enhanced warfarin interaction checker platform.

Warfarin is a common anticoagulant drug for thrombo-prophylaxis in stroke and venous thromboembolism...

Precision Risk Stratification in Atrial Fibrillation: Evaluating Machine Learning Models for Bleeding Prediction and Clinical Integration.

Proteomic Learning of Gamma-Aminobutyric Acid (GABA) Receptor-Mediated Anesthesia.

Anesthetics are crucial in surgical procedures and therapeutic interventions, but they come with sid...

Artificial Intelligence-Assisted Capsule Endoscopy Versus Conventional Capsule Endoscopy for Detection of Small Bowel Lesions: A Systematic Review and Meta-Analysis.

BACKGROUND: Capsule endoscopy (CE) is a valuable tool used in the diagnosis of small intestinal lesi...

Using Machine Learning Models to Diagnose Chronic Rhinosinusitis: Analysis of Pre-Treatment Patient-Generated Health Data to Predict Cardinal Symptoms and Sinonasal Inflammation.

BackgroundThe diagnosis of chronic rhinosinusitis (CRS) relies upon patient-reported symptoms and ob...

Machine Learning Models With Prognostic Implications for Predicting Gastrointestinal Bleeding After Coronary Artery Bypass Grafting and Guiding Personalized Medicine: Multicenter Cohort Study.

BACKGROUND: Gastrointestinal bleeding is a serious adverse event of coronary artery bypass grafting ...

Diagnostic accuracy of convolutional neural network algorithms to distinguish gastrointestinal obstruction on conventional radiographs in a pediatric population.

PURPOSE: Gastrointestinal (GI) dilatations are frequently observed in radiographs of pediatric patie...

Improving the Real-Time Classification of Disease Severity in Ulcerative Colitis: Artificial Intelligence as the Trigger for a Second Opinion.

INTRODUCTION: Endoscopic classification of ulcerative colitis (UC) shows high interobserver variatio...

Artificial intelligence models predicting abnormal uterine bleeding after COVID-19 vaccination.

The rapid deployment of COVID-19 vaccines has necessitated the ongoing surveillance of adverse event...

Machine Learning-Based Mortality Prediction for Acute Gastrointestinal Bleeding Patients Admitted to Intensive Care Unit.

OBJECTIVE: The study aimed to develop machine learning (ML) models to predict the mortality of patie...