Cardiovascular

Automated diagnosis of atherosclerosis using multi-layer ensemble models and bio-inspired optimization in intravascular ultrasound imaging.

Atherosclerosis causes heart disease by forming plaques in arterial walls. IVUS imaging provides a h...

SeqSeg: Learning Local Segments for Automatic Vascular Model Construction.

Computational modeling of cardiovascular function has become a critical part of diagnosing, treating...

Machine Learning on 50,000 Manuscripts Shows Increased Clinical Research by Academic Cardiac Surgeons.

INTRODUCTION: Academic cardiac surgeons are productive researchers and innovators. We sought to perf...

Intelligent cardiovascular disease diagnosis using deep learning enhanced neural network with ant colony optimization.

To identify patterns in big medical datasets and use Deep Learning and Machine Learning (ML) to reli...

Physiological control for left ventricular assist devices based on deep reinforcement learning.

BACKGROUND: The improvement of controllers of left ventricular assist device (LVAD) technology suppo...

Artificial intelligence in cardiology: a peek at the future and the role of ChatGPT in cardiology practice.

Artificial intelligence has increasingly become an integral part of our daily activities. ChatGPT, a...

Unsupervised Machine Learning to Identify Risk Factors of Pyeloplasty Failure in Ureteropelvic Junction Obstruction.

In adult patients with ureteropelvic junction obstruction (UPJO), little data exist on predicting p...

Sensory Stimulation and Robot-Assisted Arm Training After Stroke: A Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Functional recovery after stroke is often limited, despite various treatment...

Digital wound monitoring with artificial intelligence to prioritise surgical wounds in cardiac surgery patients for priority or standard review: protocol for a randomised feasibility trial (WISDOM).

INTRODUCTION: Digital surgical wound monitoring for patients at home is becoming an increasingly com...

Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study.

BACKGROUND: Cardiac arrest (CA) is one of the leading causes of death among patients in the intensiv...

Predicting stroke volume variation using central venous pressure waveform: a deep learning approach.

. This study evaluated the predictive performance of a deep learning approach to predict stroke volu...

Decoding Multi-Class Motor Imagery From Unilateral Limbs Using EEG Signals.

The EEG is a widely utilized neural signal source, particularly in motor imagery-based brain-compute...

Neural network reconstruction of the left atrium using sparse catheter paths.

PURPOSE: Catheter-based radiofrequency ablation for pulmonary vein isolation has become the first li...

Effective cardiac disease classification using FS-XGB and GWO approach.

Globally, cardiovascular diseases (CVDs) are a leading cause of death; however, their impact can be ...

Artificial Intelligence and Mitral Regurgitation: Friend or Foe?

Classification of coronary artery disease using radial artery pulse wave analysis via machine learning.

BACKGROUND: Coronary artery disease (CAD) is a major global cardiovascular health threat and the lea...

Accuracy of deep learning in the differential diagnosis of coronary artery stenosis: a systematic review and meta-analysis.

BACKGROUND: In recent years, as deep learning has received widespread attention in the field of hear...

Predicting structure-targeted food bioactive compounds for middle-aged and elderly Asians with myocardial infarction: insights from genetic variations and bioinformatics-integrated deep learning analysis.

Myocardial infarction (MI) is a significant global health issue. Despite the advances in genome-wide...

Machine learning approaches to identify the link between heavy metal exposure and ischemic stroke using the US NHANES data from 2003 to 2018.

PURPOSE: There is limited understanding of the link between exposure to heavy metals and ischemic st...

Development of a machine learning model to estimate length of stay in coronary artery bypass grafting.

OBJECTIVE: To develop and validate a predictive model utilizing machine-learning techniques for esti...

A Novel Bilateral Underactuated Upper Limb Exoskeleton for Post-Stroke Bimanual ADL Training.

This paper introduces a lightweight bilateral underactuated upper limb exoskeleton (UULE) designed t...