Gastroenterology

Peptic Ulcer Disease

Latest AI and machine learning research in peptic ulcer disease for healthcare professionals.

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Showing 127-147 of 3,581 articles
Proteomic Learning of Gamma-Aminobutyric Acid (GABA) Receptor-Mediated Anesthesia.

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

Endoscopists' knowledge, perceptions, and attitudes toward the use of artificial intelligence in endoscopy: a systematic review.

BACKGROUND AND AIMS: Artificial intelligence (AI) is rapidly evolving in the field of GI endoscopy. ...

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...

Identification of potential biomarkers for lung cancer using integrated bioinformatics and machine learning approaches.

Lung cancer is one of the most common cancer and the leading cause of cancer-related death worldwide...

An advanced robotic system incorporating haptic feedback for precision cardiac ablation procedures.

This study introduces an innovative master-slave cardiac ablation catheter robot system that employs...

Machine Learning Predicts Bleeding Risk in Atrial Fibrillation Patients on Direct Oral Anticoagulant.

Predicting major bleeding in nonvalvular atrial fibrillation (AF) patients on direct oral anticoagul...

Identification of Biomarkers for Response to Interferon in Chronic Hepatitis B Based on Bioinformatics Analysis and Machine Learning.

Interferon (IFN) is a pivotal agent against hepatitis B virus (HBV) in clinic, but there is a lack o...

Machine learning using random forest to differentiate between blow and fall situations of head trauma.

Blunt head trauma is a common occurrence in forensic practice. Interpreting the origin of craniocere...

An Integrative Machine Learning Model for Predicting Early Safety Outcomes in Patients Undergoing Transcatheter Aortic Valve Implantation.

: Early safety outcomes following transcatheter aortic valve implantation (TAVI) for severe aortic s...

New machine-learning models outperform conventional risk assessment tools in Gastrointestinal bleeding.

Rapid and accurate identification of high-risk acute gastrointestinal bleeding (GIB) patients is ess...

Democratizing cancer detection: artificial intelligence-enhanced endoscopy could address global disparities in head and neck cancer outcomes.

INTRODUCTION: This article explores the potential role of artificial intelligence (AI) in enhancing ...

Towards full integration of explainable artificial intelligence in colon capsule endoscopy's pathway.

Despite recent surge of interest in deploying colon capsule endoscopy (CCE) for early diagnosis of c...

Unsupervised neural network-based image stitching method for bladder endoscopy.

Bladder endoscopy enables the observation of intravesical lesion characteristics, making it an essen...

Combining machine learning with external validation to explore necroptosis and immune response in moyamoya disease.

Moyamoya disease (MMD) is a rare chronic vascular disease leads to cognitive impairment and stroke w...

SEGT-GO: a graph transformer method based on PPI serialization and explanatory artificial intelligence for protein function prediction.

BACKGROUND: A massive amount of protein sequences have been obtained, but their functions remain cha...

Use of artificial intelligence in submucosal vessel detection during third-space endoscopy.

While artificial intelligence (AI) shows high potential in decision support for diagnostic gastroint...

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