Cardiovascular

Development and validation of 10-year risk prediction models of cardiovascular disease in Chinese type 2 diabetes mellitus patients in primary care using interpretable machine learning-based methods.

AIM: To develop 10-year cardiovascular disease (CVD) risk prediction models in Chinese patients with...

Advancing Cardiovascular Health Equity With Artificial Intelligence: A Collective Ethical Responsibility.

Effects of precise cardio sounds on the success rate of phonocardiography.

This work investigates whether inclusion of the low-frequency components of heart sounds can increas...

Identifying high-risk Fontan phenotypes using K-means clustering of cardiac magnetic resonance-based dyssynchrony metrics.

BACKGROUND: Individuals with a Fontan circulation encompass a heterogeneous group with adverse outco...

Predictors of left atrial appendage thrombus in atrial fibrillation patients undergoing cardioversion.

BACKGROUND: Atrial fibrillation and atrial flutter represent the most prevalent clinically significa...

A robot-based hybrid lower limb system for Assist-As-Needed rehabilitation of stroke patients: Technical evaluation and clinical feasibility.

BACKGROUND: Although early rehabilitation is important following a stroke, severely affected patient...

A novel approach for the effective prediction of cardiovascular disease using applied artificial intelligence techniques.

AIMS: The objective of this research is to develop an effective cardiovascular disease prediction fr...

A spatio-temporal graph convolutional network for ultrasound echocardiographic landmark detection.

Landmark detection is a crucial task in medical image analysis, with applications across various fie...

Automated Quality Assessment of Medical Images in Echocardiography Using Neural Networks with Adaptive Ranking and Structure-Aware Learning.

The quality of medical images is crucial for accurately diagnosing and treating various diseases. Ho...

2-Dimensional Echocardiographic Global Longitudinal Strain With Artificial Intelligence Using Open Data From a UK-Wide Collaborative.

BACKGROUND: Global longitudinal strain (GLS) is reported to be more reproducible and prognostic than...

A Novel Implementation of a Social Robot for Sustainable Human Engagement in Homecare Services for Ageing Populations.

This research addresses the rapid aging phenomenon prevalent in Asian societies, which has led to a ...

Diagnostic accuracy of artificial intelligence in detecting left ventricular hypertrophy by electrocardiograph: a systematic review and meta-analysis.

Several studies suggested the utility of artificial intelligence (AI) in screening left ventricular ...

CapNet: An Automatic Attention-Based with Mixer Model for Cardiovascular Magnetic Resonance Image Segmentation.

Deep neural networks have shown excellent performance in medical image segmentation, especially for ...

Low energy virtual monochromatic CT with deep learning image reconstruction to improve delineation of endoleaks.

AIM: This study aimed to investigate the utility of low-energy virtual monochromatic imaging (VMI) c...

Diagnostic and Prognostic Electrocardiogram-Based Models for Rapid Clinical Applications.

Leveraging artificial intelligence (AI) for the analysis of electrocardiograms (ECGs) has the potent...

Applications of artificial intelligence in computed tomography imaging for phenotyping pulmonary hypertension.

PURPOSE OF REVIEW: Pulmonary hypertension is a heterogeneous condition with significant morbidity an...

Clinician perceptions of a novel wearable robotic hand orthosis for post-stroke hemiparesis.

PURPOSE: Wearable robotic devices are currently being developed to improve upper limb function for i...

Generative Pre-trained Transformer for Pediatric Stroke Research: A Pilot Study.

BACKGROUND: Pediatric stroke is an important cause of morbidity in children. Although research can b...

Unsupervised stochastic learning and reduced order modeling for global sensitivity analysis in cardiac electrophysiology models.

BACKGROUND AND OBJECTIVE: Numerical simulations in electrocardiology are often affected by various u...

Artificial intelligence-driven multiomics predictive model for abdominal aortic aneurysm subtypes to identify heterogeneous immune cell infiltration and predict disease progression.

BACKGROUND: Abdominal aortic aneurysm (AAA) poses a significant health risk and is influenced by var...

Detection of Endoleak after Endovascular Aortic Repair through Deep Learning Based on Non-contrast CT.

OBJECTIVES: To develop and validate a deep learning model for detecting post-endovascular aortic rep...