Cardiovascular

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

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A systematic review and meta-analysis on the performance of convolutional neural networks ECGs in the diagnosis of hypertrophic cardiomyopathy.

INTRODUCTION: Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death in younge...

Regional Image Quality Scoring for 2-D Echocardiography Using Deep Learning.

OBJECTIVE: To develop and compare methods to automatically estimate regional ultrasound image qualit...

Enhancing cardiovascular disease classification in ECG spectrograms by using multi-branch CNN.

Cardiovascular disease (CVD) is caused by the abnormal functioning of the heart which results in a h...

Machine Learning-Based predictive model for adolescent metabolic syndrome: Utilizing data from NHANES 2007-2016.

Metabolic syndrome (Mets) in adolescents is a growing public health issue linked to obesity, hyperte...

A quantum-optimized approach for breast cancer detection using SqueezeNet-SVM.

Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for ...

Identification of Novel Biomarkers for Ischemic Stroke Through Integrated Bioinformatics Analysis and Machine Learning.

Ischemic stroke leads to permanent damage to the affected brain tissue, with strict time constraints...

Pregnancy-Induced Cardiomyopathy: What Case Managers Need to Know.

A new form of stethoscope with artificial intelligence (AI) capabilities may make the difference bet...

Ledged Beam Walking Test Automatic Tracker: Artificial intelligence-based functional evaluation in a stroke model.

The quantitative evaluation of motor function in experimental stroke models is essential for the pre...

The association of lifestyle with cardiovascular and all-cause mortality based on machine learning: a prospective study from the NHANES.

BACKGROUND: Lifestyle and cardiovascular mortality and all-cause mortality have been exhaustively ex...

A comprehensive analysis of stroke risk factors and development of a predictive model using machine learning approaches.

Stroke is a leading cause of death and disability globally, particularly in China. Identifying risk ...

Elephant-inspired tapered cable-driven hyper-redundant manipulator: design and performance analysis.

The cable-driven hyper-redundant manipulator (CDHM), distinguished by its high flexibility and adjus...

Analysis of Cardiac Arrhythmias Based on ResNet-ICBAM-2DCNN Dual-Channel Feature Fusion.

Cardiovascular disease (CVD) poses a significant challenge to global health, with cardiac arrhythmia...

Clinical validation of an individualized auto-adaptative serious game for combined cognitive and upper limb motor robotic rehabilitation after stroke.

BACKGROUND: Intensive rehabilitation through challenging and individualized tasks are recommended to...

Prognosis modelling of adverse events for post-PCI treated AMI patients based on inflammation and nutrition indexes.

OBJECTIVE: This study aimed to evaluate the predictive performance of inflammatory and nutritional i...

Machine learning prediction of in-hospital mortality and external validation in patients with cardiogenic shock: the RESCUE score.

INTRODUCTION AND OBJECTIVES: Despite advances in mechanical circulatory support, mortality rates in ...

Automated vs manual cardiac MRI planning: a single-center prospective evaluation of reliability and scan times.

OBJECTIVES: Evaluating the impact of an AI-based automated cardiac MRI (CMR) planning software on pr...

An interpretable hybrid machine learning approach for predicting three-month unfavorable outcomes in patients with acute ischemic stroke.

BACKGROUND: Acute ischemic stroke (AIS) is a clinical disorder caused by nontraumatic cerebrovascula...

Multiple token rearrangement Transformer network with explicit superpixel constraint for segmentation of echocardiography.

Diagnostic cardiologists have considerable clinical demand for precise segmentation of echocardiogra...

A novel hybrid ViT-LSTM model with explainable AI for brain stroke detection and classification in CT images: A case study of Rajshahi region.

Computed tomography (CT) scans play a key role in the diagnosis of stroke, a leading cause of morbid...

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