Acute Coronary Syndrome

Methodological Approaches in the Evaluation of Platelet Structure and Function: An Instrumental Perspective.

Platelets are anucleate yet metabolically active cells that play essential roles in hemostasis, thro...

Feasibility and image quality evaluation of accelerated T2-weighted and time-of-flight MRI using AI-assisted compressed sensing and deep reconstruction.

BACKGROUND: Magnetic Resonance Imaging (MRI) provides high-resolution, non-invasive diagnostic image...

Social Determinants of Guideline-Directed Oral Anticoagulation Prescription in Patients With Atrial Fibrillation Without Contraindications: Findings From the American Heart Association Get With the Guidelines-Atrial Fibrillation Registry.

BACKGROUND: Oral anticoagulant (OAC) prescriptions recommended by atrial fibrillation guidelines to ...

Deep Learning-Based Image Reconstruction in Ultra-High-Resolution CT Venography for Improved Visualization of Cerebral Venous Drainage.

PURPOSE: To evaluate the diagnostic confidence and image quality of deep-learning-enhanced ultra-hig...

Obstetric pharmacoeconomics.

INTRODUCTION: Pharmacoeconomic principles are increasingly shaping modern obstetric pharmacology as ...

Development and Validation of an Interpretable Machine Learning Model to Predict Mortality in Patients With Sepsis-Induced Coagulopathy: Multicenter Cohort Study.

BACKGROUND: Sepsis-induced coagulopathy (SIC) is a common and severe complication in patients with s...

Interpretable prediction model for short- and long-term hepatic encephalopathy and variceal rebleeding after TIPS: a real-world study.

INTRODUCTION: Transjugular intrahepatic portosystemic shunt (TIPS) relieves portal hypertension, but...

On-Premise Detection of a Guideline-Driven Oral Anticoagulation Shift in German Doctors' Letters Using Local Large Language Models.

INTRODUCTION: A vast amount of German clinical routine data are still stored in unstructured doctors...

Machine Learning and Deep Learning in Deep Vein Thrombosis: A Narrative Review of Clinical Applications for Diagnosis, Risk Prediction, and Outcome Management.

Machine learning (ML) and deep learning (DL) are increasingly applied across the clinical spectrum o...

Dynamic Simulation and Digital Twins in Atrial Fibrillation: Complementary Roles and Current Limitations.

Atrial fibrillation (AF) management relies on established risk scores, with CHA2DS2-VASc supporting ...

Large language models fail to reliably predict emergent catheterization laboratory activation from prehospital electrocardiograms.

BACKGROUND: Rapid and accurate electrocardiogram (ECG) interpretation is essential for timely identi...

A machine learning model for predicting ischemic and bleeding risk after percutaneous coronary intervention: Development and external validation.

OBJECTIVE: This study aimed to develop and externally validate a machine learning-based risk predict...

Predicting unplanned CRRT interruptions in critically Ill burn patients using stacked ensemble machine learning framework.

Unplanned interruption of continuous renal replacement therapy (CRRT) is a frequent complication in ...

Prospective accuracy study on an artificial intelligence-based ultrasound system for gestational age estimation among pregnant women in Ghana, Kenya and South Africa: protocol.

BACKGROUND: Risk screening for pre-eclampsia relies on accurate gestational age assessment, but rout...

Explainable machine learning for neurocognitive severity clustering and multivariable profiling after acute coronary syndrome.

Neurocognitive impairment is a frequent complication of Acute Coronary Syndrome (ACS). Current resea...

Bringing AI to the Front Lines: PMcardio for Detecting Occlusive Myocardial Infarction in STEMI and STEMI-Equivalent Activations.

Clinical heterogeneity mapping and machine learning-based prediction of recurrence in gallstone disease: a retrospective cohort study of 9,939 patients.

BACKGROUND: Gallstone disease constitutes a substantial global health burden, characterized by notab...

MitoLatentProfiler: ROI-constrained deep learning for mitochondrial phenotyping in human myotubes.

Mitochondrial network organization in skeletal muscle reflects metabolic health and is disrupted in ...

Post AF Ablation Anticoagulation: Real World Practice and Predictors of Therapy.

BACKGROUND: Oral anticoagulation (OAC) is recommended for ≥3 months post catheter ablation (CA) for ...

Artificial Intelligence-Enhanced Risk Stratification in Non-ST-Segment Elevation Myocardial Infarction: The Incremental Prognostic Value of the Modified Glasgow Prognostic Score in Predicting 36-Month Mortality.

OBJECTIVE: Current clinical guidelines for non-ST-segment elevation myocardial infarction (NSTEMI) e...

Beyond Accuracy: Why Replacing Traditional Scores with AI in Thrombosis Care Creates New Ethical and Regulatory Obligations.

Clinical prediction scores have been central to thrombosis and hemostasis practice for decades, prov...