Cardiovascular

Methinks AI software for identifying large vessel occlusion in non-contrast head CT: A pilot retrospective study in American population.

BackgroundNon-contrast computed tomography (NCCT) is the first image for stroke assessment, but its ...

Carotid and femoral bifurcation plaques detected by ultrasound as predictors of cardiovascular events.

Risk factor-based algorithms give a good estimate of cardiovascular (CV) risk at the population leve...

Convolutional Neural Network Fused With Recurrent Network for ECG-Based Detection of Hypertrophic Cardiomyopathy.

BACKGROUND: Hypertrophic Cardiomyopathy (HCM) affects the left ventricle of the heart, leading to th...

HERGAI: an artificial intelligence tool for structure-based prediction of hERG inhibitors.

The human Ether-à-go-go-Related Gene (hERG) potassium channel is crucial for repolarizing the cardia...

Machine learning identification of key genes in cardioembolic stroke and atherosclerosis: their association with pan-cancer and immune cells.

BACKGROUND: Cardioembolic stroke (CS) and atherosclerosis (AS) are closely related diseases. Ferropt...

Effects and neural mechanisms of a brain-computer interface-controlled soft robotic glove on upper limb function in patients with subacute stroke: a randomized controlled fNIRS study.

BACKGROUND AND PURPOSE: The brain-computer interface-based soft robotic glove (BCI-SRG) holds promis...

Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients.

BACKGROUND: Coronary artery disease (CAD) remains a leading cause of global mortality, with stroke c...

Association of initial core volume on non-contrast CT using a deep learning algorithm with clinical outcomes in acute ischemic stroke: a potential tool for selection and prognosis?

BACKGROUND: In an extended time window, contrast-based neuroimaging is valuable for treatment select...

Pre-interventional transesophageal echocardiography as a reliable predictor of residual shunt following patent foramen ovale closure.

BACKGROUND: Closure of a patent foramen ovale (PFO) is an effective strategy in the prevention of re...

A Dynamic Machine Learning Model to Predict Angiographic Vasospasm After Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND AND OBJECTIVES: The goal of this study was to develop a highly precise, dynamic machine l...

Artificial intelligence fully automated analysis of handheld echocardiography in real-world patients with suspected heart failure.

AIMS: Echocardiography is a rate-limiting step in the timely diagnosis of heart failure (HF). Automa...

Post-stroke aphasia analysis using topological alterations in brain functional networks.

. Nearly one-third of stroke patients develop aphasia. Although the function of classical language a...

Clinical diagnostic and prognostic value of homocysteine combined with hemoglobin [f (Hcy-Hb)] in cardio-renal syndrome caused by primary acute myocardial infarction.

BACKGROUND: Cardio-renal syndrome (CRS), characterized by multi-organ interaction, is frequently ove...

Deep learning-based prognosis of major adverse cardiac events in patients with acute myocardial infarction: a retrospective observational study in the Republic of Korea.

OBJECTIVES: This study developed deep neural network (DNN) models capable of accurately classifying ...

Explainable machine learning model for predicting functional outcomes in posterior circulation stroke after thrombectomy.

BACKGROUND: The early prediction of functional outcomes in patients with posterior circulation strok...

Artificial intelligence-powered advancements in atrial fibrillation diagnostics: a systematic review.

BACKGROUND: Cardiovascular diseases remain one of the leading causes of mortality worldwide, with at...

Back to the Future-Cardiovascular Imaging From 1966 to Today and Tomorrow.

This article, on the 60th anniversary of the journal Investigative Radiology, a journal dedicated to...

A commentary on "Prognostic value of iron-metabolism biomarkers in critically ill patients with atrial fibrillation: a machine learning-based retrospective cohort study".

Letter to editor about "prognostic value of iron-metabolism biomarkers in critically ill patients with atrial fibrillation: a machine learning-based retrospective cohort study".

CTA-Derived Plaque Characteristics and Risk of Acute Coronary Syndrome in Patients With Coronary Artery Calcium Score of Zero: Insights From the ICONIC Trial.

. Coronary artery calcium (CAC) scoring is used to stratify acute coronary syndrome (ACS) risk. None...

Factors influencing the performance of cardiopulmonary resuscitation by lay rescuers: A qualitative study based on the Theory of Planned Behavior.

AIMS: This study investigated the underlying causes for the current low rate of cardiopulmonary resu...