Cardiovascular

Myocardial Perfusion PET-CT: There's More Here Than Meets the (A)I.

Effect of low-dose colchicine on pericoronary inflammation and coronary plaque composition in chronic coronary disease: a subanalysis of the LoDoCo2 trial.

BACKGROUND: Low-dose colchicine (0.5 mg once daily) reduces the risk of major cardiovascular events ...

Comprehensive bioinformatics analysis and experimental verification identify mitochondrial gene Dgat2 as a novel therapeutic biomarker for myocardial ischemia-reperfusion.

BACKGROUND: Ischemic cardiomyopathy is a severe disease marked by high morbidity and mortality, ofte...

Identification of diagnostic genes for myocardial ischemia reperfusion injury associated with metabolic syndrome through the integration of bioinformatics analysis, molecular docking and experimental validation.

BACKGROUND: Metabolic dysregulation in metabolic syndrome (MetS) exacerbates myocardial ischemia-rep...

Association between the stress hyperglycemia ratio and all-cause mortality in patients with hemorrhagic stroke: a retrospective analysis based on MIMIC-IV database.

BACKGROUND: Research on the associations between the stress hyperglycemia ratio (SHR) and adverse ou...

Bioinformatics-based screening of genes associated with dilated cardiomyopathy.

BACKGROUND: Due to the lack of appropriate diagnostic biomarkers and intervention targets, the diagn...

High burden of premature ventricular contractions upregulates transcriptional markers of inflammation and promotes adverse cardiac remodeling linked to cardiomyopathy.

Premature ventricular contractions (PVCs) are the most prevalent ventricular arrhythmia in adults. H...

Artificial intelligence-enhanced electrocardiogram diastolic function grade predicts post-septal myectomy mortality in hypertrophic cardiomyopathy.

BACKGROUNDS: Diastolic dysfunction is an important pathophysiologic feature of hypertrophic cardiomy...

Fully automated Bayesian analysis for quantifying the extent and distribution of pulmonary perfusion changes on CT pulmonary angiography in CTEPH.

OBJECTIVES: This work aimed to develop an automated method for quantifying the distribution and seve...

MicroRNA signature predicts post operative atrial fibrillation after coronary artery bypass grafting.

Early detection of atrial fibrillation (AFib) is crucial for altering its natural progression and co...

Deep Learning-Based Fully Automated Aortic Valve Leaflets and Root Measurement From Computed Tomography Images　- A Feasibility Study.

BACKGROUND: The aim of this study was to retrain our existing deep learning-based fully automated ao...

Knowledge-Driven Graph Representation Learning for Myocardial Infarction Localization.

The electrocardiogram (ECG) serves as a crucial tool for myocardial infarction (MI) localization, an...

Deep Separable Spatiotemporal Learning for Fast Dynamic Cardiac MRI.

OBJECTIVE: Dynamic magnetic resonance imaging (MRI) plays an indispensable role in cardiac diagnosis...

Complex Fractionated Atrial Electrograms, Dispersion, and Voltage in Persistent Atrial Fibrillation: Implications for Electrogram-Guided Ablation.

BACKGROUND: Various methods have been used to identify substrate of persistent atrial fibrillation (...

Multiscale Organization of Neural Networks in a 3D Bioprinted Matrix.

The efficient establishment of in vitro neural models that accurately mimic the structural and funct...

Blood pressure monitoring is key in aortic dissection.

Blood pressure (BP) control is essential for both the prevention and long-term management of aortic ...

Advanced predictive modeling for enhanced mortality prediction in ICU stroke patients using clinical data.

Background Stroke is second-leading cause of disability and death among adults. Approximately 17 mil...

Machine learning models of depression in middle-aged and older adults with cardiovascular metabolic diseases.

BACKGROUND: The incidence of cardiovascular metabolic diseases (CMD) is increasing, and depression i...

Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning.

IMPORTANCE: Traditional methods of surgical decision making heavily rely on human experience and pro...

From the stethoscope to artificial intelligence: decoding tricuspid disease.

Hypertension precision medicine: the promise and pitfalls of pharmacogenomics.

Pharmacogenomics (PGx) has the potential to revolutionize hypertension management by tailoring antih...