Acute Coronary Syndrome

Medication Extraction from Electronic Clinical Notes in an Integrated Health System: A Study on Aspirin Use in Patients with Nonvalvular Atrial Fibrillation.

PURPOSE: The purpose of this study was to investigate whether aspirin use can be captured from the c...

Novel, Precise, Accurate Ion-Pairing Method to Determine the Related Substances of the Fondaparinux Sodium Drug Substance: Low-Molecular-Weight Heparin.

Fondaparinux sodium is a synthetic low-molecular-weight heparin (LMWH). This medication is an antico...

Comparison of model-based and expert-rule based electrocardiographic identification of the culprit artery in patients with acute coronary syndrome.

BACKGROUND AND PURPOSE: Culprit coronary artery assessment in the triage ECG of patients with suspec...

Inhibitory effects of total saponin from Korean Red Ginseng on [Ca(2+)]i mobilization through phosphorylation of cyclic adenosine monophosphate-dependent protein kinase catalytic subunit and inositol 1,4,5-trisphosphate receptor type I in human platelets.

BACKGROUND: Intracellular Ca(2+)([Ca(2+)]i) is a platelet aggregation-inducing molecule. Therefore, ...

A Synergistic Role of Myeloperoxidase and High Sensitivity Troponin T in the Early Diagnosis of Acute Coronary Syndrome.

Aim of this study was to evaluate the role of Myeloperoxidase (MPO) and high sensitive Troponin T in...

Prevalence of aspirin resistance in Asian-Indian patients with stable coronary artery disease.

OBJECTIVE: To evaluate the prevalence of pharmacological resistance to aspirin therapy by measuring ...

A novel method of adverse event detection can accurately identify venous thromboembolisms (VTEs) from narrative electronic health record data.

BACKGROUND: Venous thromboembolisms (VTEs), which include deep vein thrombosis (DVT) and pulmonary e...

Early Detection of Acute Coronary Syndrome Using a Mobile Digital Health Application.

Early detection of acute coronary syndrome (ACS) is vital for reducing ischemic time and preserving ...

Validation of the ACS-NSQIP surgical risk calculator for patients with paraoesophageal hernias undergoing robotic repair.

BACKGROUND: The National Surgical Quality Improvement Program (NSQIP) American College of Surgeons (...

Insights on Scan-Specific Deep-Learning Strategies for Brain MRI Parallel Imaging Reconstruction.

Scan-specific deep learning strategies have been proposed for parallel imaging reconstruction in whi...

Anticoagulation colloidal microrobots based on heparin-mimicking polymers.

Coagulation within blood vessels is a major cause of cardiovascular disease and global mortality, hi...

Enhancing Drug-Target Interaction Prediction through Transfer Learning from Activity Cliff Prediction Tasks.

Recently, machine learning (ML) has gained popularity in the early stages of drug discovery. This tr...

Detection of large areas of thin-cap fibroatheroma in a recurrent STEMI patient using a novel artificial intelligence algorithm: moving from 2D to 3D.

Bleeding risk assessment tools in patients with atrial fibrillation taking anticoagulants: a comparative review and clinical implications.

INTRODUCTION: Bleeding risk assessment plays a critical role in the anticoagulation management for a...

Error correcting 2D-3D cascaded network for myocardial infarct scar segmentation on late gadolinium enhancement cardiac magnetic resonance images.

Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) imaging is considered the in vivo...

MACHINE LEARNING AND BIOINFORMATICS TO IDENTIFY COAGULATION BIOMARKERS IN SEPSIS-RELATED KIDNEY INJURY.

Background: Sepsis-associated acute kidney injury (SA-AKI) is a life-threatening complication with m...

Re-engineering the clinical approach to suspected cardiac chest pain assessment in the emergency department by expediting research evidence to practice using artificial intelligence. (RAPIDx AI)-a cluster randomized study design.

BACKGROUND: Clinical work-up for suspected cardiac chest pain is resource intensive. Despite expecta...

MACHINE LEARNING AND SHOCK INDICES-DERIVED SCORE FOR PREDICTING CONTRAST-INDUCED NEPHROPATHY IN ACUTE CORONARY SYNDROME PATIENTS.

Background: Contrast-induced nephropathy (CIN) is a serious complication following acute coronary sy...

Accurate and efficient machine learning interatomic potentials for finite temperature modelling of molecular crystals.

As with many parts of the natural sciences, machine learning interatomic potentials (MLIPs) are revo...

Machine learning models based on a national-scale cohort accurately identify patients at high risk of deep vein thrombosis following primary total hip arthroplasty.

BACKGROUND: The occurrence of deep venous thrombosis (DVT) following total hip arthroplasty (THA) po...

Cutting Skill Assessment by Motion Analysis Using Deep Learning and Spatial Marker Tracking.

The assessment of surgical skill is crucial for indicating a surgeon's proficiency. While motion ana...