Peptic Ulcer Disease

Precision Medicine for Anticoagulation Strategies in the Cath Lab: Part 2.

PURPOSE OF REVIEW: Intraprocedural anticoagulation during percutaneous coronary intervention (PCI) remains particularly challenging in high-risk and underrepresented populations, where the balance between thrombotic and bleeding risk is complex and often unpredictable. This review summarizes contemporary evidence and remaining knowledge gaps regarding anticoagulant selection, dosing, and monitorin...

Artificial intelligence assessment of endoscopic severity and extent: A machine learning approach to continuous evaluation of endoscopic inflammation in ulcerative colitis.

BACKGROUND: The endoscopy subscore is a therapeutic endpoint in ulcerative colitis trials but is limited by reader variability and inability to fully capture the degree of inflammation across the colon. We developed the artificial intelligence assessment of endoscopic severity and extent (AI-ESe), a continuous, more granular assessment of inflammation throughout the colon to better capture the tot...

Preliminary Analysis of Biomarkers and Molecular Mechanisms in Graves' ophthalmopathy Patients Related to the Retinol Metabolic Pathway.

OBJECTIVE: This study aimed to identify potential biomarkers for Graves' ophthalmopathy (GO) through bioinformatics analyses and to validate their exp...

The VISION-AI Trial: protocol for a pragmatic randomized controlled non-inferiority trial comparing artificial intelligence-guided colonoscopy to pancolonic chromoendoscopy for neoplasia detection in adults with colorectal inflammatory bowel disease.

BACKGROUND: Current guidelines recommend pancolonic chromoendoscopy (pCE) over white light endoscopy (WLE) alone for colorectal neoplasia (CRN) detect...

SPPIPred: Stacking-based ensemble learning model for identification of protein-protein interaction.

Protein-protein interactions (PPIs) are essential for various biological functions and are crucial in drug discovery, signaling pathways, and network ...

Development and validation of a routine blood test-based model to predict in-hospital postoperative pulmonary infection in older patients with hip fracture.

BACKGROUND: Postoperative pulmonary infection (PPI) is a common and serious complication in older adults undergoing hip fracture surgery, leading to p...

Using Artificial Intelligence to Identify Patterns and Predictors of Adverse Drug Reactions in Cardiovascular Patients: A Comprehensive Narrative Review.

Artificial intelligence (AI) has emerged as a transformative tool for improving the detection, prediction, and prevention of adverse drug reactions (A...

A machine learning approach to non-invasive prediction of hepatic decompensation in compensated advanced chronic liver disease: the CIRI model.

BACKGROUND & AIMS: Hepatic venous pressure gradient (HVPG) is the gold standard for assessment of prognosis in compensated advanced chronic liver dise...

Response to correspondence on 'Evaluation of the impact of NOAC underdosing and exploration of bleeding risk factors in elderly patients with atrial fibrillation: artificial intelligence-based approach' by Protzenko et al.

Prognosis Prediction and Shared Decision Making for Personalised Anticoagulant Therapy after Unprovoked Venous Thromboembolism: The MORPHEUS project.

Background In patients with unprovoked venous thromboembolism (VTE), indefinite anticoagulation is recommended to prevent recurrence but may expose so...

VITAGRAPH: building a knowledge graph for biologically relevant learning tasks.

The complexity of human biology poses ongoing challenges, driving global interdisciplinary research. Artificial intelligence has become a powerful too...

Transformer-DAPT: AI-based dynamic assessment of ischemic and bleeding risks in patients on DAPT following PCI.

Dual antiplatelet therapy (DAPT) following percutaneous coronary intervention (PCI) is traditionally guided by rule-based scores providing static, sin...

Identification of ITGB2, ELN, and KLRK1 as stress granule-related biomarkers of pterygium through integrated transcriptomic analysis and machine learning.

BACKGROUND: Stress granules (SGs) play a crucial role in cellular stress responses, but their involvement remains unclear in pterygium. This study aim...

AI meets sleep surgery: assessing drug-induced sleep endoscopy interpretation with a large language model.

STUDY OBJECTIVES: To evaluate the performance and safety of a large language model in interpreting drug-induced sleep endoscopy (DISE) videos and prov...

From Prediction to Action: Why Bleeding Risk in Cardiac Surgery Still Eludes Us in the Era of Artificial Intelligence.

Perioperative bleeding in cardiac surgery remains common, consequential, and difficult to predict despite decades of research and expanding data avail...

The slope of enlightenment: Towards a more realistic understanding of the strengths and weaknesses of artificial intelligence for colorectal polyp assessment.

Artificial intelligence (AI) has rapidly evolved into a transformative adjunct to gastrointestinal (GI) endoscopy, particularly through deep-learning-...

Evaluation of deep learning-based reconstruction models on non-TOF BGO PET/CT: impact of acquisition times and BSREM penalization factors on lesion detectability and SNR.

BACKGROUND: New long field-of-view (FOV) PET scanners using bismuth germanate (BGO) detectors without time-of-flight (TOF) capability are now availabl...

Towards transparent and reliable AI in gastroenterology: pragmatic recommendations for evaluation and reporting.

Artificial intelligence (AI) is expanding in gastroenterology, particularly in endoscopy and imaging, where models support detection, classification, ...

Integrating epigenetic and metabolic indicators for non-invasive endometrial cancer triage: a machine learning approach.

OBJECTIVE: Abnormal uterine bleeding (AUB) is a primary symptom indicative of endometrial cancer (EC), yet its diagnosis still primarily relies on inv...

A vision transformer deep learning model for assessing pediatric ileocolic intussusception severity using ultrasound images.

Timely identification of children with ileocolic intussusception likely to fail air-enema reduction is critical to avoid delays and bowel perforation....