Cardiovascular

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

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Machine learning algorithms to predict heart failure with preserved ejection fraction among patients with premature myocardial infarction.

BACKGROUND: Heart Failure with Preserved Ejection Fraction (HFpEF) in patients with Premature Myocar...

Machine learning models for predicting survival in lung cancer patients undergoing microwave ablation.

OBJECTIVE: To develop and validate predictive models assessing survival outcomes in patients with no...

Using machine learning models to predict post-revascularization thrombosis in PAD.

BACKGROUND: Graft/ stent thrombosis after lower extremity revascularization (LER) is a serious compl...

Prediction of perimetric progression in ocular hypertension and open angle glaucoma based on corneal biomechanics.

PurposeTo identify parameters that are significant risk predictors of visual field (VF) progression ...

Invited Article: Al guided Dual Antiplatelet Therapy and Anticoagulation.

Artificial intelligence (AI) has emerged as a transformative tool in healthcare through data analysi...

A Review on Intelligent Systems for ECG Analysis: From Flexible Sensing Technology to Machine Learning.

This paper conducts an extensive review of flexible cardiac sensing devices designed for electrocard...

Advancing cardiovascular care through actionable AI innovation.

Despite significant advances, the prevention and management of cardiovascular disease remain challen...

An efficient patient's response predicting system using multi-scale dilated ensemble network framework with optimization strategy.

The forecasting of a patient's response to radiotherapy and the likelihood of experiencing harmful l...

Enhancing Cardiopulmonary Resuscitation Quality Using a Smartwatch: Neural Network Approach for Algorithm Development and Validation.

BACKGROUND: Sudden cardiac arrest is a major cause of mortality, necessitating immediate and high-qu...

Optimizing Stroke Risk Prediction: A Primary Dataset-Driven Ensemble Classifier With Explainable Artificial Intelligence.

BACKGROUND AND AIMS: Stroke remains a leading cause of mortality and long-term disability worldwide,...

The Role of Artificial Intelligence in Providing Real-Time Guidance During Interventional Cardiology Procedures: A Narrative Review.

Integrating artificial intelligence (AI) in interventional cardiology revolutionizes procedural guid...

Determining the biomarkers and pathogenesis of myocardial infarction combined with ankylosing spondylitis via a systems biology approach.

Ankylosing spondylitis (AS) is linked to an increased prevalence of myocardial infarction (MI). Howe...

Effects of exoskeleton rehabilitation robot training on neuroplasticity and lower limb motor function in patients with stroke.

BACKGROUND: Lower limb exoskeleton rehabilitation robot is a new technology to improve the lower lim...

Prediction of intradialytic hypotension by machine learning: A systematic review.

BACKGROUND: Intradialytic hypotension is associated with increased morbidity, and mortality. Several...

Multitask learning multimodal network for chronic disease prediction.

Chronic diseases are a critical focus in the management of elderly health. Early disease prediction ...

Multi-objective optimization framework to plan laser ablation procedure for prostate tumors through a genetic algorithm.

BACKGROUND AND OBJECTIVES: Prostate cancer is the most common form of cancer in the male population....

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