Acute Coronary Syndrome

The use of artificial neural network analysis can improve the risk-stratification of patients presenting with suspected deep vein thrombosis.

Artificial neural networks are machine-learning algorithms designed to analyse data without a pre-existing hypothesis as to any associations that may exist. This technique has not previously been applied to the risk stratification of patients referred with suspected deep vein thrombosis (DVT). Current assessment is usually with a points-based clinical score, which may be combined with a D-dimer bl...

Ultrasensitive sandwich-type immunosensor for cardiac troponin I based on enhanced electrocatalytic reduction of HO using β-cyclodextrins functionalized 3D porous graphene-supported Pd@Au nanocubes.

In this study, Pd@Au nanocubes supported β-cyclodextrins functionalized three-dimensional porous graphene (CDs-3D-PG-Pd@Au NCs) was synthesized using a facile method. β-cyclodextrins (CDs) were beneficial in improving the dispersibility of three-dimensional porous graphene (3D-PG) and displayed good capture capability towards secondary antibodies (Ab). Moreover, large amounts of Pd@Au NCs could lo...

Automated selection of myocardial inversion time with a convolutional neural network: Spatial temporal ensemble myocardium inversion network (STEMI-NET).

PURPOSE: Delayed enhancement imaging is an essential component of cardiac MRI, which is used widely for the evaluation of myocardial scar and viabilit...

Utilizing dynamic treatment information for MACE prediction of acute coronary syndrome.

BACKGROUND: Main adverse cardiac events (MACE) are essentially composite endpoints for assessing safety and efficacy of treatment processes of acute c...

Physicochemical property based computational scheme for classifying DNA sequence elements of Saccharomyces cerevisiae.

GenerationE of huge "omics" data necessitates the development and application of computational methods to annotate the data in terms of biological fea...

Postmarketing surveillance on clinical use of edoxaban in patients with nonvalvular atrial fibrillation (ETNA-AF-Japan): Three-month interim analysis results.

BACKGROUND: Direct oral anticoagulants are the first-line drugs for anticoagulation therapy in nonvalvular atrial fibrillation (NVAF). However, a real...

Cardiac Troponin I: Ultrasensitive Detection Using Faradaic Electrochemical Impedance.

An electrochemical biosensor for the detection of cardiac troponin I, cTnI, an important cardiac biomarker, is described. A combination of a novel mon...

Anticoagulant Related Nephropathy Induced by Dabigatran.

We describe a case of biopsy-proven dabigatran related nephropathy in a patient without underlying IgA nephropathy. To date, dabigatran related nephro...

Using Machine Learning to Predict the Information Seeking Behavior of Clinicians Using an Electronic Medical Record System.

Poor electronic medical record (EMR) usability is detrimental to both clinicians and patients. A better EMR would provide concise, context sensitive p...

Machine-learned models using hematological inflammation markers in the prediction of short-term acute coronary syndrome outcomes.

BACKGROUND: Increased systemic and local inflammation play a vital role in the pathophysiology of acute coronary syndrome. This study aimed to assess ...

Adversarial MACE Prediction After Acute Coronary Syndrome Using Electronic Health Records.

Acute coronary syndrome (ACS), as an emergent and severe syndrome due to decreased blood flow in the coronary arteries, is a leading cause of death an...

Antithrombotic Management during Percutaneous Mitral Valve Repair with the Mitraclip System in a Patient with Heparin-Induced Thrombocytopenia.

Interventional cardiology procedures require full anticoagulation to prevent thrombus formation on catheters and devices with potential development of...

Ensemble of machine learning algorithms using the stacked generalization approach to estimate the warfarin dose.

Warfarin dosing remains challenging due to narrow therapeutic index and highly individual variability. Incorrect warfarin dosing is associated with de...

Therapeutic Enoxaparin in the Morbidly Obese Patient: A Case Report and Review of the Literature.

Enoxaparin is a low molecular weight heparin commonly used in the treatment of venous thromboembolisms (VTEs); however, evidence on optimal empiric do...

Scan-specific robust artificial-neural-networks for k-space interpolation (RAKI) reconstruction: Database-free deep learning for fast imaging.

PURPOSE: To develop an improved k-space reconstruction method using scan-specific deep learning that is trained on autocalibration signal (ACS) data.

Analytical Concordance of Diverse Point-of-Care and Central Laboratory Troponin I Assays.

BACKGROUND: Cardiac troponin I (cTnI) 99th percentile cutoffs, used in the diagnosis of acute myocardial infarction, are not standardized across cTnI ...

Real-time microrobot posture recognition via biplane X-ray imaging system for external electromagnetic actuation.

PURPOSE: As a promising intravascular therapeutic approach for autonomous catheterization, especially for thrombosis treatment, a microrobot or roboti...

Low Protein Z Level: A Thrombophilic Risk Biomarker for Acute Coronary Syndrome.

Acute coronary syndrome (ACS) encompasses a range of thrombotic coronary artery diseases. Protein Z (PZ)/PZ-dependent protease inhibitor complex is a ...

Autonomous detection, grading, and reporting of postoperative complications using natural language processing.

INTRODUCTION: Natural language processing, a computer science technique that allows interpretation of narrative text, is infrequently used to identify...

Effect of Health and Training on Ultrasensitive Cardiac Troponin in Marathon Runners.

PURPOSE: Cardiac troponin (cTn) is the gold standard biomarker for assessing cardiac damage. Previous studies have demonstrated increases in plasma cT...