Cardiovascular

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

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Eeg Microstates and Balance Parameters for Stroke Discrimination: A Machine Learning Approach.

Electroencephalography microstates (EEG-MS) show promise to be a neurobiological biomarker in stroke...

Can artificial intelligence lower the global sudden cardiac death rate? A narrative review.

PURPOSE OF REVIEW: WHO defines SCD as sudden unexpected death either within 1 h of symptom onset (wi...

Lean body mass and stroke volume, a sex issue.

INTRODUCTION: Large vessel occlusions (LVO) account for over 60% of stroke-related mortality and dis...

Artificial intelligence-enhanced comprehensive assessment of the aortic valve stenosis continuum in echocardiography.

BACKGROUND: Transthoracic echocardiography (TTE) is the primary modality for diagnosing aortic steno...

Deep learning for the classification of atrial fibrillation using wavelet transform-based visual images.

BACKGROUND: As the incidence and prevalence of Atrial Fibrillation (AF) proliferate worldwide, the c...

Satisfactory Evaluation of Call Service Using AI After Ureteral Stent Insertion: Randomized Controlled Trial.

BACKGROUND: Ureteral stents, such as double-J stents, have become indispensable in urologic procedur...

Predicting doxorubicin-induced cardiotoxicity in breast cancer: leveraging machine learning with synthetic data.

Doxorubicin (DOXO) is a primary treatment for breast cancer but can cause cardiotoxicity in over 25%...

Multiscale feature enhanced gating network for atrial fibrillation detection.

BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is a significant cause of life-threatening heart ...

Opportunistic AI for enhanced cardiovascular disease risk stratification using abdominal CT scans.

This study introduces the Deep Learning-based Cardiovascular Disease Incident (DL-CVDi) score, a nov...

Research on predicting radiographic exposure time in imaging based on neural network prediction models.

OBJECTIVE: To explore the anatomical and clinical factors that affect the radiographic exposure time...

Machine learning-driven prediction of medical expenses in triple-vessel PCI patients using feature selection.

Revascularization therapies, such as percutaneous coronary intervention (PCI) and coronary artery by...

Key Concepts in Machine Learning and Clinical Applications in the Cardiac Intensive Care Unit.

PURPOSE OF REVIEW: Artificial Intelligence (AI) technology will significantly alter critical care ca...

Advances in the Application of Artificial Intelligence in the Ultrasound Diagnosis of Vulnerable Carotid Atherosclerotic Plaque.

Vulnerable atherosclerotic plaque is a type of plaque that poses a significant risk of high mortalit...

TagGen: Diffusion-based generative model for cardiac MR tagging super resolution.

PURPOSE: The aim of the work is to develop a cascaded diffusion-based super-resolution model for low...

Deep learning-aided diagnosis of acute abdominal aortic dissection by ultrasound images.

PURPOSE: Acute abdominal aortic dissection (AD) is a serious disease. Early detection based on ultra...

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