Cardiovascular

Artificial intelligence for direct-to-physician reporting of ambulatory electrocardiography.

Developments in ambulatory electrocardiogram (ECG) technology have led to vast amounts of ECG data t...

Contrast-enhanced magnetic resonance imaging based calf muscle perfusion and machine learning in peripheral artery disease.

Peripheral artery disease (PAD) remains underdiagnosed and undertreated and is associated with an in...

Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review.

BACKGROUND: Although catheter ablation (CA) is currently the most effective clinical treatment for a...

Pseudo-HFOs Elimination in iEEG Recordings Using a Robust Residual-Based Dictionary Learning Framework.

High-frequency oscillations (HFOs) in intracranial EEG (iEEG) recordings are critical biomarkers for...

Comparing Phenotypes for Acute and Long-Term Response to Atrial Fibrillation Ablation Using Machine Learning.

BACKGROUND: It is difficult to identify patients with atrial fibrillation (AF) most likely to respon...

SleepECG-Net: Explainable Deep Learning Approach With ECG for Pediatric Sleep Apnea Diagnosis.

Obstructive sleep apnea (OSA) in children is a prevalent and serious respiratory condition linked to...

Enhancing machine learning performance in cardiac surgery ICU: Hyperparameter optimization with metaheuristic algorithm.

The healthcare industry is generating a massive volume of data, promising a potential goldmine of in...

[Investigation of impedance drop during lesions created by robot-assisted radiofrequency ablation].

Integration of single-cell and bulk RNA sequencing data using machine learning identifies oxidative stress-related genes LUM and PCOLCE2 as potential biomarkers for heart failure.

Oxidative stress (OS) is a pivotal mechanism driving the progression of cardiovascular diseases, par...

Advancements and challenges in high-sensitivity cardiac troponin assays: diagnostic, pathophysiological, and clinical perspectives.

Although significant progress has been made in recent years, some important questions remain regardi...

Network Analysis and Machine Learning for Signal Detection and Prioritization Using Electronic Healthcare Records and Administrative Databases: A Proof of Concept in Drug-Induced Acute Myocardial Infarction.

BACKGROUND: Safety signals for potential drug-induced adverse events (AEs) typically emerge from mul...

Energy-Confinement 3D Flower-Shaped Cages for AI-Driven Decoding of Metabolic Fingerprints in Cardiovascular Disease Diagnosis.

Rapid and accurate detection plays a critical role in improving the survival and prognosis of patien...

Predicting cardiovascular outcomes in Chinese patients with type 2 diabetes by combining risk factor trajectories and machine learning algorithm: a cohort study.

BACKGROUND: Cardiovascular complications are major concerns for Chinese patients with type 2 diabete...

Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence.

The relevance of the study is due to the growing number of diseases of the cerebrovascular system, i...

Characterisation of cardiovascular disease (CVD) incidence and machine learning risk prediction in middle-aged and elderly populations: data from the China health and retirement longitudinal study (CHARLS).

BACKGROUND: Due to the ageing population and evolving lifestyles occurring in China, middle-aged and...

A two-branch framework for blood pressure estimation using photoplethysmography signals with deep learning and clinical prior physiological knowledge.

This paper presents a novel dual-branch framework for estimating blood pressure (BP) using photoplet...

Machine Learning-Driven Discovery of Structurally Related Natural Products as Activators of the Cardiac Calcium Pump SERCA2a.

A key molecular dysfunction in heart failure is the reduced activity of the cardiac sarcoplasmic ret...

TQGDNet: Coronary artery calcium deposit detection on computed tomography.

Coronary artery disease (CAD) continues to be a leading global cause of cardiovascular related morta...

A comparative analysis of Constant-Q Transform, gammatonegram, and Mel-spectrogram techniques for AI-aided cardiac diagnostics.

Cardiovascular diseases (CVDs) are the leading global cause of death, which requires the early and a...

CaBind_MCNN: Identifying Potential Calcium Channel Blocker Targets by Predicting Calcium-Binding Sites in Ion Channels and Ion Transporters Using Protein Language Models and Multiscale Feature Extraction.

Calcium ions (Ca) are crucial for various physiological processes, including neurotransmission and c...

Effects of Gait Rehabilitation Robot Combined with Electrical Stimulation on Spinal Cord Injury Patients' Blood Pressure.

BACKGROUND: Orthostatic hypotension can occur during acute spinal cord injury (SCI) and subsequently...