Cardiovascular

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

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Machine learning for predicting acute myocardial infarction in patients with sepsis.

Acute myocardial infarction (AMI) and sepsis are the leading causes of high mortality rates in inten...

The role of the dorsomedial hypothalamus in the cardiogenic sympathetic reflex in the Sprague Dawley rat.

Myocardial ischemia causes the production and release of metabolites such as bradykinin, which stimu...

Machine Learning-Driven Identification of Distinct Persistent Atrial Fibrillation Phenotypes: A Cluster Analysis of DECAAF II.

INTRODUCTION: Catheter ablation of persistent atrial fibrillation yields sub-optimal success rates p...

Identifying the presence of atrial fibrillation during sinus rhythm using a dual-input mixed neural network with ECG coloring technology.

BACKGROUND: Undetected atrial fibrillation (AF) poses a significant risk of stroke and cardiovascula...

Predicting upper limb motor recovery in subacute stroke patients via fNIRS-measured cerebral functional responses induced by robotic training.

BACKGROUND: Neural activation induced by upper extremity robot-assisted training (UE-RAT) helps char...

Optimizing hypertension prediction using ensemble learning approaches.

Hypertension (HTN) prediction is critical for effective preventive healthcare strategies. This study...

Automated measurement of cardiothoracic ratio based on semantic segmentation integration model using deep learning.

The objective of this study is to investigate the efficacy of the semantic segmentation model in pre...

Using clinical data to reclassify ESUS patients to large artery atherosclerotic or cardioembolic stroke mechanisms.

PURPOSE: Embolic stroke of unidentified source (ESUS) represents 10-25% of all ischemic strokes. Our...

sJAM-C as a Potential Biomarker for Coronary Artery Stenosis: Insights from a Clinical Study in Coronary Heart Disease Patients.

PURPOSE: Coronary artery stenosis caused by atherogenesis is a major pathological link in coronary h...

Machine learning based radiomics model to predict radiotherapy induced cardiotoxicity in breast cancer.

PURPOSE: Cardiotoxicity is one of the major concerns in breast cancer treatment, significantly affec...

Pinning down the accuracy of physics-informed neural networks under laminar and turbulent-like aortic blood flow conditions.

BACKGROUND: Physics-informed neural networks (PINNs) are increasingly being used to model cardiovasc...

Reliability of post-contrast deep learning-based highly accelerated cardiac cine MRI for the assessment of ventricular function.

OBJECTIVE: The total examination time can be reduced if high-quality two-dimensional (2D) cine image...

Accurate Arrhythmia Classification with Multi-Branch, Multi-Head Attention Temporal Convolutional Networks.

Electrocardiogram (ECG) signals contain complex and diverse features, serving as a crucial basis for...

Detecting cardiovascular diseases using unsupervised machine learning clustering based on electronic medical records.

BACKGROUND: Electronic medical records (EMR)-trained machine learning models have the potential in C...

Predicting Early recurrence of atrial fibrilation post-catheter ablation using machine learning techniques.

BACKGROUND: Catheter ablation is a common treatment for atrial fibrillation (AF), but recurrence rat...

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