Cardiovascular

Speech decoding from stereo-electroencephalography (sEEG) signals using advanced deep learning methods.

Brain-computer interfaces (BCIs) are technologies that bypass damaged or disrupted neural pathways a...

Identification of immune-related genes and small-molecule drugs in hypertension-induced left ventricular hypertrophy based on machine learning algorithms and molecular docking.

BACKGROUND: Left ventricular hypertrophy (LVH) is a common consequence of hypertension and can lead ...

Identification of endoplasmic reticulum stress genes in human stroke based on bioinformatics and machine learning.

After ischemic stroke (IS), secondary injury is intimately linked to endoplasmic reticulum (ER) stre...

Development and validation of a machine learning predictive model for perioperative myocardial injury in cardiac surgery with cardiopulmonary bypass.

BACKGROUND: Perioperative myocardial injury (PMI) with different cut-off values has showed to be ass...

Machine learning-based model development for predicting risk factors of prolonged intra-aortic balloon pump therapy in patients with coronary artery bypass grafting.

Machine learning algorithms are frequently used to clinical risk prediction. Our study was designed ...

A machine learning model predicts stroke associated with blood cadmium level.

Stroke is the leading cause of death and disability worldwide. Cadmium is a prevalent environmental ...

Neural network aided extended Kalman filtering for inverse imaging of cardiac transmembrane potential.

The aim of this study is to address the limitations in reconstructing the electrical activity of the...

Motion robust coronary MR angiography using zigzag centric ky-kz trajectory and high-resolution deep learning reconstruction.

PURPOSE: To develop a new MR coronary angiography (MRCA) technique by employing a zigzag fan-shaped ...

Multi-grained contrastive representation learning for label-efficient lesion segmentation and onset time classification of acute ischemic stroke.

Ischemic lesion segmentation and the time since stroke (TSS) onset classification from paired multi-...

Artificial Intelligence Based Methods to Enhance Analysis of Non-Contrast Computed Tomography in Patients with Aortic Aneurysm.

nnU-Net-based deep-learning for pulmonary embolism: detection, clot volume quantification, and severity correlation in the RSPECT dataset.

OBJECTIVES: CT pulmonary angiography is the gold standard for diagnosing pulmonary embolism, and DL ...

CMRxRecon: A publicly available k-space dataset and benchmark to advance deep learning for cardiac MRI.

Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac disea...

Integrating machine learning approach to identify sleep-disordered breathing in hypertrophic cardiomyopathy.

Machine learning-based detection of sleep-disordered breathing in hypertrophic cardiomyopathy.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is often concomitant with sleep-disordered breathing (...

The premise, promise, and perils of artificial intelligence in critical care cardiology.

Artificial intelligence (AI) is an emerging technology with numerous healthcare applications. AI cou...

[Artificial intelligence in cardiovascular radiology : Image acquisition, image reconstruction and workflow optimization].

BACKGROUND: Artificial intelligence (AI) has the potential to fundamentally change radiology workflo...

Robot-aided assessment and associated brain lesions of impaired ankle proprioception in chronic stroke.

BACKGROUND: Impaired ankle proprioception strongly predicts balance dysfunction in chronic stroke. H...

The role of artificial intelligence in cardiovascular magnetic resonance imaging.

Cardiovascular magnetic resonance (CMR) imaging is the gold standard test for myocardial tissue char...

Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence-review of evidence and proposition of a roadmap to clinical translation.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessm...

The beating heart: artificial intelligence for cardiovascular application in the clinic.

Artificial intelligence (AI) integration in cardiac magnetic resonance imaging presents new and exci...

Inter-Rater and Intra-Rater Agreement in Scoring Severity of Rodent Cardiomyopathy and Relation to Artificial Intelligence-Based Scoring.

We previously developed a computer-assisted image analysis algorithm to detect and quantify the micr...