Peptic Ulcer Disease

Integrated ore classification using stand-alone and hybridised machine learning algorithms.

A state-of-the-art, robust classification model using artificial intelligence (AI) algorithms was developed in this study to estimate the gold ore classes based on trace elements measured by inductively coupled plasma (ICP). This approach involves the utilisation of stand-alone machine learning (ML) algorithms integrated within a committee machine (CM) framework. To this end, 19 trace elements inc...

Artificial Intelligence Applications in COVID-19-Associated Coagulopathy: Lessons Learned.

Coronavirus disease 2019 (COVID-19)-associated coagulopathy (CAC) is a thromboinflammatory syndrome marked by endothelial injury, micro- and macrovascular thrombosis, and, in a minority, late consumptive bleeding. D-dimer elevation was found to be one of the most consistent laboratory abnormalities and an established marker of severity. In this review, we explore how artificial intelligence method...

In silico discovery of selective TPX2 and BUB1B inhibitors as novel antimitotic agents in breast cancer therapy.

Breast cancer (BC) is one of the most common malignancies in women globally, characterized by significant genetic and clinical heterogeneity. This com...

Probing uric acid-related prognostic genes and their molecular mechanisms in prostate cancer based on transcriptomic data.

Recent studies highlight the role of uric acid in tumor development, but its impact on prostate cancer (PCa) remains underexplored. This study aimed t...

Glioblastoma diagnostic models and therapeutic drug discovery based on GEO data and machine learning methods.

BACKGROUND: Glioblastoma (GBM) remains lethal due to high molecular heterogeneity and treatment resistance. While previous studies have proposed vario...

Integrated bioinformatics and machine learning, research on specific biomarkers for large-artery atherosclerosis stroke.

Large-artery atherosclerosis stroke (LAA) is the main subtype of ischemic stroke. Currently, the diagnosis of LAA is confirmed through magnetic resona...

When seconds matter - introducing a surgical salvage strategy by emergency robotic surgery: a review.

Robotic surgery has expanded minimally invasive options but introduces specific vulnerabilities during intraoperative emergencies. The physical separa...

Phase diagram and global structure search of bismuth using machine learning potential.

Bismuth's (Bi) unique high-pressure phase behavior has long attracted significant interest. Despite their significance in both technological applicati...

Embedding artificial intelligence literacy in endoscopy training: extending the European Society of Gastrointestinal Endoscopy (ESGE) curriculum framework.

Exploring exosome-related genes as candidate biomarkers in primary immune thrombocytopenia through transcriptomics and preliminary experimental validation.

Primary Immune Thrombocytopenia (ITP) is an autoimmune disease characterized by thrombocytopenia and bleeding tendency. Exosomes mediate abnormal cros...

Machine learning-based models using preoperative imaging and clinical data to predict intraoperative rebleeding and functional recovery in intracerebral hemorrhage patients: a multicenter study.

BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is associated with high mortality and disability. This study aimed to develop and validate mach...

Effect of a clinical decision support system on stroke care quality and outcomes in patients with acute ischaemic stroke (GOLDEN BRIDGE II): cluster randomised clinical trial.

OBJECTIVE: To evaluate the efficacy of a clinical decision support system (CDSS) on stroke care quality and clinical outcomes among patients with acut...

INTELCAPE: A Deep Learning-Powered System for Automated, High-Accuracy Crohn's Disease Diagnosis via Capsule Endoscopy.

BACKGROUND & AIMS: Capsule endoscopy (CE) is a noninvasive technique for diagnosing Crohn's disease (CD); however, manual interpretation of CE videos ...

Artificial intelligence in medicine: a scoping review of the risk of deskilling and loss of expertise among physicians.

BACKGROUND: Artificial intelligence (AI) systems are increasingly deployed in clinical practice, particularly in radiology, pathology, endoscopy, and ...

Artificial intelligence in inflammatory bowel disease: bridging innovation, implementation and impact.

Artificial intelligence (AI) is rapidly transforming the management landscape of inflammatory bowel disease (IBD). While early applications in endosco...

Percutaneous coronary intervention in high bleeding risk patients: a review of contemporary management strategies.

INTRODUCTION: High bleeding risk (HBR) affects over one-third of patients undergoing percutaneous coronary intervention (PCI) and is associated with e...

Gene expression and metadata based identification of key genes for lung cancer, COPD, and IPF using machine learning and statistical models.

Lung cancer (LC) is one of the most prevalent and deadly cancers globally, presenting a major public health challenge. Patients with chronic obstructi...

Artificial intelligence and capsule endoscopy.

The advent of artificial intelligence (AI) is revolutionizing today's clinical practice, particularly in gastroenterology, where capsule endoscopy (CE...

Application value of gastric contrast ultrasonography in gastric tumors.

In recent years, gastric oral contrast ultrasonography (OCUS) and double contrast-enhanced ultrasonography (DCEUS) have emerged as promising imaging t...

A critical review of technical progress, clinical heterogeneity, and implementation challenges of artificial intelligence in digestive endoscopy.

INTRODUCTION: Digestive endoscopy is a critical modality for diagnosing and managing gastrointestinal diseases, yet it faces challenges including oper...