Cardiovascular

Latest AI and machine learning research in cardiovascular for healthcare professionals.

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ProtoASNet: Comprehensive evaluation and enhanced performance with uncertainty estimation for aortic stenosis classification in echocardiography.

Aortic stenosis (AS) is a prevalent heart valve disease that requires accurate and timely diagnosis ...

Preoperative submaximal cardiopulmonary exercise testing and its association with early postoperative complications.

BACKGROUND: Early postoperative complication risk prediction would enhance perioperative surveillanc...

Advancing Cardiovascular, Kidney, and Metabolic Medicine: A Narrative Review of Insights and Innovations for the Future.

Cardiovascular, kidney and metabolic (CKM) conditions are interrelated, significantly contributing t...

perfDSA: Automatic Perfusion Imaging in Cerebral Digital Subtraction Angiography.

PURPOSE: Cerebral digital subtraction angiography (DSA) is a standard imaging technique in image-gui...

Artificial intelligence in cardiovascular practice.

Artificial intelligence (AI) is everywhere, but how is this expansive technology being used in cardi...

Optimising coronary imaging decisions with machine learning: an external validation study.

BACKGROUND: Exclusion of coronary stenosis in individuals with suggestive symptoms is challenging. C...

Construction and validation of prognostic model for ICU mortality in cardiac arrest patients: an interpretable machine learning modeling approach.

BACKGROUND: The incidence and mortality of cardiac arrest (CA) is high. We developed interpretable m...

Exploring hypoxia driven subtypes of pulmonary arterial hypertension through transcriptomics single cell sequencing and machine learning.

Pulmonary arterial hypertension (PAH) is a progressive cardiovascular disease characterized by eleva...

Predicting outcomes following open abdominal aortic aneurysm repair using machine learning.

Patients undergoing open surgical repair of abdominal aortic aneurysm (AAA) have a high risk of post...

A robotic rehabilitation intervention in a home setting during the Covid-19 outbreak: a feasibility pilot study in patients with stroke.

BACKGROUND: Telerehabilitation allows patients to engage in therapy away from healthcare facilities,...

Data-driven sleep structure deciphering based on cardiorespiratory signals.

BACKGROUND AND OBJECTIVE: Cardiorespiratory signals provide a novel perspective for understanding sl...

Deep learning-based post hoc denoising for 3D volume-rendered cardiac CT in mitral valve prolapse.

We hypothesized that deep learning-based post hoc denoising could improve the quality of cardiac CT ...

Deep learning can predict cardiovascular events from liver imaging.

BACKGROUND & AIMS: Cardiovascular mortality remains the leading cause of death and a significant sou...

Integrating WGCNA and SVM-RFE identifies hub molecular biomarkers driving ischemic stroke progression.

BACKGROUND: Stroke is the second most common cause of death worldwide and the leading cause of long-...

Post-stroke spontaneous motor recovery in mice can be predicted from acute-phase local field potential using machine learning.

Stroke remains a leading cause of long-term disability, underscoring the urgent need for effective p...

Plaque burden improves the detection of ischemic CAD over stenosis from coronary computed tomography angiography.

In symptomatic patients undergoing coronary CTA for suspected coronary artery disease (CAD), we asse...

Machine learning to risk stratify chest pain patients with non-diagnostic electrocardiogram in an Asian emergency department.

INTRODUCTION: Elevated troponin, while essential for diagnosing myocardial infarction, can also be p...

A wearable ankle-assisted robot for improving gait function and pattern in stroke patients.

BACKGROUND: Hemiplegic gait after a stroke can result in a decreased gait speed and asymmetrical gai...

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