Acute Coronary Syndrome

Equiflow: An open-source software package for evaluating changes in cohort composition.

Clinical research studies routinely apply exclusion criteria and data preprocessing steps that can s...

Magnetically controlled capsule endoscopy: Innovations, standardized practice, and emerging clinical roles.

Capsule endoscopy has transformed small bowel evaluation but remains limited for gastric examination...

A novel predictive model for evaluating thrombus regression in postpartum venous thromboembolism patients.

INTRODUCTION: Antithrombotic evaluation of postpartum venous thromboembolism (VTE) after anticoagula...

Multimorbidity and major adverse cardiovascular events in antipsychotic users: Time-to-event prediction by explainable machine learning.

Antipsychotic treatment is associated with higher risk of major adverse cardiovascular events (MACEs...

Exploratory prediction model for deep vein thrombosis in intensive care patients after anticoagulation therapy: An observational study.

BACKGROUND: Despite low-molecular-weight heparin (LMWH) prophylaxis, the incidence of deep vein thro...

Development and validation of an interpretable machine learning model for predicting portal vein system thrombosis following splenectomy in Wilson's disease.

Retrieval-Augmented Language Models for Patient-Centered Periprocedural Anticoagulation in Interventional Radiology.

PURPOSE: This study evaluates Large Language Models (LLMs) integrated with Retrieval-Augmented Gener...

Early Versus Delayed Anticoagulation in Acute Ischaemic Stroke with Atrial Fibrillation According to Infarct Volume and Location: a Prespecified Subgroup Analysis of the OPTIMAS Randomised Controlled Trial.

BackgroundRandomised trials have demonstrated that early anticoagulation after acute atrial fibrilla...

Assessing the Predictive Value of Kolmogorov-Arnold Networks for the No-Reflow Phenomenon in ST-Segment Elevation Myocardial Infarction: A Comparative Machine Learning Study.

OBJECTIVE: The no-reflow phenomenon in ST-segment elevation myocardial infarction (STEMI) is a signi...

Machine learning survival model for personalised prevention of catheter-related thrombosis in tumour patients.

BACKGROUND: Central venous catheters for drug delivery introduce catheter-related thrombosis (CRT) a...

Interpretable Machine Learning for Feature-Based Classification of Platelet Activation in Rotary Blood Pumps.

BACKGROUND: Thrombosis in rotary blood pumps arises from complex flow conditions that remain difficu...

Multiphysics learning with graph neural networks for thrombosis prediction in intracranial aneurysms.

Intracranial aneurysms are pathological dilations of cerebral arteries affecting 3-5% of the populat...

Machine learning-based prediction of myocardial ischemia-reperfusion injury in patients with ST-segment elevation myocardial infarction: the STEMI-MIRI prediction model.

Beyond Percutaneous Coronary Intervention - Targeted Molecular Therapies for the Next Era of Coronary Care.

Coronary artery disease (CAD) remains the leading global cause of cardiovascular morbidity and morta...

Advanced neuroimaging for central nervous system infections: when, where, how, and why?

PURPOSE OF REVIEW: Central nervous system (CNS) infections remain a major cause of morbidity and mor...

AI-Enhanced Electrocardiogram for Detection of Occlusive Myocardial Infarction in High-Risk Non-ST-Segment Elevation Acute Coronary Syndrome.

BACKGROUND: Whether an artificial intelligence-enhanced electrocardiogram (AI-ECG) improves detectio...

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

Coronavirus disease 2019 (COVID-19)-associated coagulopathy (CAC) is a thromboinflammatory syndrome ...

Performance of Artificial Intelligence-Powered ECG Analysis in Suspected ST-Segment Elevation Myocardial Infarction.

BACKGROUND: Artificial intelligence (AI)-based electrocardiogram (ECG) analysis has emerged as a pro...

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 co...

Interpretable Clinical-Radiomics Model for Prediction of Blood Stasis and Left Atrial Appendage Thrombus.

BACKGROUND: The left atrial (LA) morphological profile, anatomically contiguous with the left atrial...

Establishing the laboratory error database: rationale, methodology, and a practical example.

Laboratory errors represent a critical yet underestimated threat to patient safety, with 26-30 % of ...