Cardiovascular

Deep learning of movement behavior profiles and their association with markers of cardiometabolic health.

BACKGROUND: Traditionally, existing studies assessing the health associations of accelerometer-measu...

Automatic thoracic aorta calcium quantification using deep learning in non-contrast ECG-gated CT images.

Thoracic aorta calcium (TAC) can be assessed from cardiac computed tomography (CT) studies to improv...

Gated cardiac CT in infants: What can we expect from deep learning image reconstruction algorithm?

BACKGROUND: ECG-gated cardiac CT is now widely used in infants with congenital heart disease (CHD). ...

Reproducibility of artificial intelligence-enabled plaque measurements between systolic and diastolic phases from coronary computed tomography angiography.

OBJECTIVES: Current coronary CT angiography (CTA) guidelines suggest both end-systolic and mid-diast...

Artificial intelligence-based quantitative coronary angiography of major vessels using deep-learning.

BACKGROUND: Quantitative coronary angiography (QCA) offers objective and reproducible measures of co...

Deep Learning Image Reconstruction for Transcatheter Aortic Valve Implantation Planning: Image Quality, Diagnostic Performance, Contrast volume and Radiation Dose Assessment.

RATIONALE AND OBJECTIVES: To assess image quality, contrast volume and radiation dose reduction pote...

Improved Arterial Stiffness Indices 3 and 6 Months after Living-donor Renal Transplantation.

Arterial stiffness is a non-traditional risk factor of cardiovascular disease and may explain part o...

Diagnostic performance of deep learning to exclude coronary stenosis on CT angiography in TAVI patients.

We evaluated the diagnostic performance of a deep-learning model (DLM) (CorEx®, Spimed-AI, Paris, Fr...

Segmentation-based cardiomegaly detection based on semi-supervised estimation of cardiothoracic ratio.

The successful integration of neural networks in a clinical setting is still uncommon despite major ...

Cine-cardiac magnetic resonance to distinguish between ischemic and non-ischemic cardiomyopathies: a machine learning approach.

OBJECTIVE: This work aimed to derive a machine learning (ML) model for the differentiation between i...

A fully automated artificial intelligence-driven software for planning of transcatheter aortic valve replacement.

BACKGROUND: Transcatheter aortic valve replacement (TAVR) is increasingly performed for the treatmen...

A Survey on Blood Pressure Measurement Technologies: Addressing Potential Sources of Bias.

Regular blood pressure (BP) monitoring in clinical and ambulatory settings plays a crucial role in t...

Deep learning-based diffusion tensor cardiac magnetic resonance reconstruction: a comparison study.

In vivo cardiac diffusion tensor imaging (cDTI) is a promising Magnetic Resonance Imaging (MRI) tech...

Intraoperative Features Improve Model Risk Predictions After Coronary Artery Bypass Grafting.

BACKGROUND: Intraoperative physiologic parameters could offer predictive utility in evaluating risk ...

Impact of ECG data format on the performance of machine learning models for the prediction of myocardial infarction.

Background We aim to determine which electrocardiogram (ECG) data format is optimal for ML modelling...

Artificial intelligence in preventive cardiology.

Artificial intelligence (AI) is a field of study that strives to replicate aspects of human intellig...

Natural language processing to phenotype coronary computed tomography angiography: Development, validation, and initial results of a large multi-institution cohort.

AI-Defined Cardiac Anatomy Improves Risk Stratification of Hybrid Perfusion Imaging.

BACKGROUND: Computed tomography attenuation correction (CTAC) improves perfusion quantification of h...

Circadian assessment of heart failure using explainable deep learning and novel multi-parameter polar images.

BACKGROUND AND OBJECTIVE: Heart failure (HF) is a multi-faceted and life-threatening syndrome that a...

Sensor-Based Measurement Method to Support the Assessment of Robot-Assisted Radiofrequency Ablation.

Digital surgery technologies, such as interventional robotics and sensor systems, not only improve p...

Uncertainty-aware deep learning for trustworthy prediction of long-term outcome after endovascular thrombectomy.

Acute ischemic stroke (AIS) is a leading global cause of mortality and morbidity. Improving long-ter...