Latest AI and machine learning research in acute coronary syndrome for healthcare professionals.
BACKGROUND: Robust Artificial-neural-networks for k-space Interpolation (RAKI) is a recently proposed deep-learning-based reconstruction algorithm for parallel imaging. Its main premise is to perform k-space interpolation using convolutional neural networks (CNNs) trained on subject-specific autocalibration signal (ACS) data. Since training is performed individually for each subject, the reconstru...
We investigated clinical significance of cell-free DNA (cfDNA) in heart failure. This study enrolled 32 heart failure patients and 28 control subjects. Total cfDNA levels were not different between groups (P = 0.343). Bisulfite-digital polymerase chain reaction using the unmethylated FAM101A locus demonstrated that cardiomyocyte-specific cfDNA was significantly elevated in heart failure patients c...
A sensitive and simple liquid chromatography-tandem mass spectrometry method was developed and validated for the simultaneous quantification of ticagr...
Thrombosis development in either arterial or venous system remains a major cause of death and disability worldwide. This poorly controlled in vivo clo...
BACKGROUND: Machine learning (ML) encompasses a wide variety of methods by which artificial intelligence learns to perform tasks when exposed to data....
Thrombotic events are one of the leading causes of mortality and morbidity related to cancer, with ovarian cancer having one of the highest incidence ...
PURPOSE: Vulnerable plaque detection is important to acute coronary syndrome (ACS) diagnosis. In recent years, intravascular optical coherence tomogra...
BACKGROUND: Computerised electrocardiogram (ECG) interpretation diagnostic algorithms have been developed to guide clinical decisions like with ST seg...
OBJECTIVE: Photoselective vaporization of the prostate (PVP) is a widely performed surgical procedure for benign prostatic obstruction. This approach ...
BACKGROUND: Venous thromboembolism is a common disease seen in the emergency department and a cause of high morbidity and mortality, constituting a ma...
BACKGROUND: The aim of this study was to develop a diagnostic prediction model to improve identification of acute symptomatic portal vein thrombosis (...
OBJECTIVES: Congestive heart failure (CHF) is a heart disease with a growing incidence and prevalence. Creatine kinase-myocardial base (CK-MB) is gene...
The aim of this study is to predict acute coronary syndrome (ACS) requiring revascularization in those patients presenting early-stage angina-like sym...
OBJECTIVES: When caring for children in a hospital setting, tablets are often manipulated at the ward to obtain the right dose. One example is manipul...
OBJECTIVE: Deep vein thrombosis (DVT) is a disease caused by abnormal blood clots in deep veins. Accurate segmentation of DVT is important to facilita...
OBJECTIVE: The aim of this study was to conduct an effective assessment of peripherally inserted central venous catheter (PICC)-related thrombosis bas...
Investigation of the clinical potential of extensive phenotype data and machine learning (ML) in the prediction of mortality in acute coronary syndro...
There is paucity of literature about the validation of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) sur...
BACKGROUND: Interconnections between major cardiovascular events (MCVEs) and renal events are recognized in diabetes, however, the specific impact of ...
BACKGROUND: Major adverse cardiac event (MACE) prediction plays a key role in providing efficient and effective treatment strategies for patients with...