Cardiovascular

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

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Deep learning methods for clinical workflow phase-based prediction of procedure duration: a benchmark study.

This study evaluates the performance of deep learning models in the prediction of the end time of pr...

CECRel: A joint entity and relation extraction model for Chinese electronic medical records of coronary angiography via contrastive learning.

Entity and relation extraction from Chinese electronic medical records (EMRs) is a crucial foundatio...

Constitutive neural networks for main pulmonary arteries: discovering the undiscovered.

Accurate modeling of cardiovascular tissues is crucial for understanding and predicting their behavi...

Artificial Intelligence to Enhance Precision Medicine in Cardio-Oncology: A Scientific Statement From the American Heart Association.

Artificial intelligence is poised to transform cardio-oncology by enabling personalized care for pat...

Atrial fibrillation risk model based on LASSO and SVM algorithms and immune infiltration of key mitochondrial energy metabolism genes.

Atrial fibrillation (AF) is a predominant cardiac arrhythmia with unclear etiology. This study used ...

Natural language processing of electronic medical records identifies cardioprotective agents for anthracycline induced cardiotoxicity.

In this retrospective observational study, we aimed to investigate the potential of natural language...

Intraoperative stenosis detection in X-ray coronary angiography via temporal fusion and attention-based CNN.

BACKGROUND AND OBJECTIVE: Coronary artery disease (CAD), the leading cause of mortality, is caused b...

The Evolving Paradigm of Myocardial Infarction in the Era of Artificial Intelligence.

The classification and treatment of myocardial infarction (MI) have evolved significantly over the p...

Novel Robotic Balloon-Based Device for Wrist-Extension Therapy of Hemiparesis Stroke Patients.

Upper-limb paresis is one of the main complications after stroke. It is commonly associated with imp...

Deep learning and electrocardiography: systematic review of current techniques in cardiovascular disease diagnosis and management.

This paper reviews the recent advancements in the application of deep learning combined with electro...

Towards Rapid and Low-Cost Stroke Detection Using SERS and Machine Learning.

Stroke affects approximately 12 million individuals annually, necessitating swift diagnosis to avert...

Machine learning-based prediction of post-induction hypotension: identifying risk factors and enhancing anesthesia management.

BACKGROUND: Post-induction hypotension (PIH) increases surgical complications including myocardial i...

Traditional and machine learning models for predicting haemorrhagic transformation in ischaemic stroke: a systematic review and meta-analysis.

BACKGROUND: Haemorrhagic transformation (HT) is a severe complication after ischaemic stroke, but id...

Identification of crucial genes for polycystic ovary syndrome and atherosclerosis through comprehensive bioinformatics analysis and machine learning.

OBJECTIVE: To identify potential biomarkers in patients with polycystic ovary syndrome (PCOS) and at...

Machine Learning in Intravascular Ultrasound: Validating Automated Lesion Assessment for Complex Coronary Interventions.

BACKGROUND: Intravascular ultrasound (IVUS) is essential for assessing complex coronary lesions, but...

Utilizing 12-lead electrocardiogram and machine learning to retrospectively estimate and prospectively predict atrial fibrillation and stroke risk.

BACKGROUND: The stroke risk in patients with subclinical atrial fibrillation (AF) is underestimated....

Explainable paroxysmal atrial fibrillation diagnosis using an artificial intelligence-enabled electrocardiogram.

BACKGROUND/AIMS: Atrial fibrillation (AF) significantly contributes to global morbidity and mortalit...

An Integrative Machine Learning Model for Predicting Early Safety Outcomes in Patients Undergoing Transcatheter Aortic Valve Implantation.

: Early safety outcomes following transcatheter aortic valve implantation (TAVI) for severe aortic s...

EffNet: an efficient one-dimensional convolutional neural networks for efficient classification of long-term ECG fragments.

Early Diagnosis of Cardiovascular disease (CVD) is essential to prevent a person from death in case ...

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