Cardiovascular

Artificial Intelligence in Nuclear Cardiology: An Update and Future Trends.

Myocardial perfusion imaging (MPI), using either single photon emission computed tomography (SPECT) ...

Automatic multi-view pose estimation in focused cardiac ultrasound.

Focused cardiac ultrasound (FoCUS) is a valuable point-of-care method for evaluating cardiovascular ...

Artificial intelligence to improve the diagnosis of pulmonary hypertension: promises and pitfalls.

Early prediction of ventricular peritoneal shunt dependency in aneurysmal subarachnoid haemorrhage patients by recurrent neural network-based machine learning using routine intensive care unit data.

Aneurysmal subarachnoid haemorrhage (aSAH) can lead to complications such as acute hydrocephalic con...

[Validation of Optimal Imaging Conditions for Coronary Computed Tomography Angiography Using High-definition Mode and Deep Learning Image Reconstruction Algorithm].

PURPOSE: To verify the optimal imaging conditions for coronary computed tomography angiography (CCTA...

Association between deep learning measured retinal vessel calibre and incident myocardial infarction in a retrospective cohort from the UK Biobank.

BACKGROUND: Cardiovascular disease is a leading cause of global death. Prospective population-based ...

Cardiac Tamponade Caused By Carbon Dioxide Insufflation During Robot-Assisted Thoracic Surgery: A Case Report.

Various complications can occur during robot-assisted thoracic surgery for mediastinal tumors owing ...

Predictive analytics for cardiovascular patient readmission and mortality: An explainable approach.

BACKGROUND: Cardiovascular patients experience high rates of adverse outcomes following discharge fr...

A hybrid neural ordinary differential equation model of the cardiovascular system.

In the human cardiovascular system (CVS), the interaction between the left and right ventricles of t...

Predicting hypertension control using machine learning.

Hypertension is a widely prevalent disease and uncontrolled hypertension predisposes affected indivi...

A deep learning method to identify and localize large-vessel occlusions from cerebral digital subtraction angiography.

BACKGROUND AND PURPOSE: An essential step during endovascular thrombectomy is identifying the occlud...

Deep learning-assisted intelligent wearable precise cardiovascular monitoring system.

Machine learning approach using F-FDG-PET-radiomic features and the visibility of right ventricle F-FDG uptake for predicting clinical events in patients with cardiac sarcoidosis.

OBJECTIVES: To investigate the usefulness of machine learning (ML) models using pretreatment F-FDG-P...

Effect of different targets of goal-directed fluid therapy on intraoperative hypotension and fluid infusion in robot-assisted laparoscopic gynecological surgery: a randomized non-inferiority trial.

Carotid corrected flow time (FTc) and tidal volume challenge pulse pressure variation (VtPPV) are us...

Diffusion-/perfusion-weighted imaging fusion to automatically identify stroke within 4.5 h.

OBJECTIVES: We aimed to develop machine learning (ML) models based on diffusion- and perfusion-weigh...

Artificial intelligence predicts undiagnosed atrial fibrillation in patients with embolic stroke of undetermined source using sinus rhythm electrocardiograms.

BACKGROUND: Artificial intelligence (AI)-enabled sinus rhythm (SR) electrocardiogram (ECG) interpret...

Artificial-intelligence-based risk prediction and mechanism discovery for atrial fibrillation using heart beat-to-beat intervals.

BACKGROUND: Early diagnosis of atrial fibrillation (AF) is important for preventing stroke and other...

US2Mask: Image-to-mask generation learning via a conditional GAN for cardiac ultrasound image segmentation.

Cardiac ultrasound (US) image segmentation is vital for evaluating clinical indices, but it often de...

A Pilot Study Using Machine-learning Algorithms and Wearable Technology for the Early Detection of Postoperative Complications After Cardiothoracic Surgery.

OBJECTIVE: To evaluate whether a machine-learning algorithm (ie, the "NightSignal" algorithm) can be...

Artificial intelligence: The future for multimodality imaging of right ventricle.

The crucial pathophysiological and prognostic roles of the right ventricle in various diseases have ...

Cross-sectional angle prediction of lipid-rich and calcified tissue on computed tomography angiography images.

PURPOSE: The assessment of vulnerable plaque characteristics and distribution is important to strati...