Cardiovascular

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

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Sub-1-min relaxation-enhanced non-contrast non-triggered cervical MRA using compressed SENSE with deep learning reconstruction in healthy volunteers.

BACKGROUND: We evaluated the acceleration of a three-dimensional isotropic flow-independent magnetic...

Artificial intelligence-enhanced retinal imaging as a biomarker for systemic diseases.

Retinal images provide a non-invasive and accessible means to directly visualize human blood vessels...

Application of Artificial Intelligence in Acute Ischemic Stroke: A Scoping Review.

Artificial intelligence (AI) is revolutionizing stroke care by enhancing diagnosis, treatment, and o...

Rapid wall shear stress prediction for aortic aneurysms using deep learning: a fast alternative to CFD.

Aortic aneurysms pose a significant risk of rupture. Previous research has shown that areas exposed ...

Antifreezing Ultrathin Bioionic Gel-Based Wearable System for Artificial Intelligence-Assisted Arrhythmia Diagnosis in Hypothermia.

Cardiovascular disease (CAD) is a major global public health issue, with mortality rates being signi...

Research on the development of an intelligent prediction model for blood pressure variability during hemodialysis.

OBJECTIVE: Blood pressure fluctuations during dialysis, including intradialytic hypotension (IDH) an...

Diagnosis of Benign and Malignant Newly Developed Nodules on the Surgical Side After Breast Cancer Surgery Based on Machine Learning.

To enhance the diagnostic accuracy of new nodules on the surgical side after breast cancer surgery ...

Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review.

BACKGROUND: Transcatheter aortic valve implantation (TAVI) therapy has demonstrated its clear benefi...

Use of machine learning models to identify National Institutes of Health-funded cardiac arrest research.

OBJECTIVE: To compare the performance of three artificial intelligence (AI) classification strategie...

Enhanced heart failure mortality prediction through model-independent hybrid feature selection and explainable machine learning.

Heart failure (HF) remains a significant public health challenge with high mortality rates. Machine ...

Stress hyperglycemia ratio and machine learning model for prediction of all-cause mortality in patients undergoing cardiac surgery.

BACKGROUND: The stress hyperglycemia ratio (SHR) was developed to reduce the effects of long-term ch...

Predicting major adverse cardiac events in diabetes and chronic kidney disease: a machine learning study from the Silesia Diabetes-Heart Project.

BACKGROUND: People living with diabetes mellitus (DM) and chronic kidney disease (CKD) are at signif...

CT-based detection of clinically significant portal hypertension predicts post-hepatectomy outcomes in hepatocellular carcinoma.

BACKGROUND: While the CT-based method of detecting clinically significant portal hypertension (CSPH)...

Thermo-responsive and phase-separated hydrogels for cardiac arrhythmia diagnosis with deep learning algorithms.

Adhesive epidermal hydrogel electrodes are essential for achieving robust signal transduction and ca...

A machine learning based death risk analysis and prediction of ST-segment elevation myocardial infarction (STEMI) patients.

Acute myocardial infarction is a condition in which a part of the heart muscle cannot receive enough...

Artificial intelligence for individualized treatment of persistent atrial fibrillation: a randomized controlled trial.

Although pulmonary vein isolation (PVI) has become the cornerstone ablation procedure for atrial fib...

Ontology-guided machine learning outperforms zero-shot foundation models for cardiac ultrasound text reports.

Big data can revolutionize research and quality improvement for cardiac ultrasound. Text reports are...

Transformer-based heart language model with electrocardiogram annotations.

This paper explores the potential of transformer-based foundation models to detect Atrial Fibrillati...

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