Cardiovascular

Prediction of depression risk in middle-aged and elderly Cardiovascular-Kidney-Metabolic syndrome patients by social and environmental determinants of health: an interpretable machine learning approach using longitudinal data from China.

BACKGROUND: Cardiovascular-Kidney-Metabolic (CKM) syndrome is a systemic disease characterized by pa...

Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.

Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis...

Identification of key proteins and pathways in myocardial infarction using machine learning approaches.

Acute myocardial infarction (AMI) is a leading cause of global morbidity and mortality, requiring de...

Automated interpretation of cardiotocography using deep learning in a nationwide multicenter study.

Timely detection of abnormal cardiotocography (CTG) during labor plays a crucial role in enhancing f...

A high-throughput analysis of novel anti-fibrotics in human adult cardiac fibroblasts.

Myocardial fibrosis, a hallmark of heart failure (HF), contributes to disease progression and mortal...

Energy consumption analysis and prediction in exercise training based on accelerometer sensors and deep learning.

This study aims to enhance the accuracy and efficiency of energy consumption prediction during exerc...

Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation.

OBJECTIVE: Left atrial thrombus (LAT) poses a significant risk for stroke and other thromboembolic c...

Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis.

Diabetes Mellitus is a chronic metabolic disorder affecting a substantial global population leading ...

Identifying clinical phenotype clusters in patients with coronary artery disease.

BACKGROUND: Guideline recommendations for the prevention of cardiovascular (CV) events in patients w...

DiaBD: A diabetes dataset for enhanced risk analysis and research in Bangladesh.

Diabetes is a chronic condition affecting millions worldwide and severely impacts health and quality...

Explainable Artificial Intelligence in Radiological Cardiovascular Imaging-A Systematic Review.

Artificial intelligence (AI) and deep learning are increasingly applied in cardiovascular imaging. ...

Subclinical atrial fibrillation prediction based on deep learning and strain analysis using echocardiography.

Subclinical atrial fibrillation (SCAF), also known as atrial high-rate episodes (AHREs), refers to a...

Incorporating the STOP-BANG questionnaire improves prediction of cardiovascular events during hospitalization after myocardial infarction.

Obstructive sleep apnea (OSA) may impact outcomes in acute coronary syndrome (ACS) patients. The Glo...

Stroke Sensitivity Calculation in Medical Emergency Calls and Factors Associated With Stroke Suspicion: A Retrospective Registry-Based Study.

STUDY OBJECTIVE: Sensitivity for stroke detection in emergency medical communication centers (EMCCs)...

Predicting the Higher Energy Need for Effective Defibrillation Using Machine Learning Based on an Animal Model.

: Early defibrillation improves outcomes in cardiac arrest, but the optimal defibrillation strategy ...

Leveraging Artificial Intelligence to Bridge the Gap Between Evidence and Practice in Cardiology.

Developing an ML-Based Pretest Probability Model of Obstructive CAD in Patients With Stable Chest Pain.

BACKGROUND: Updated pretest probability models (ESC2019, the PTP model supported by the European Soc...

The Impact of Model-based Deep-learning Reconstruction Compared with that of Compressed Sensing-Sensitivity Encoding on the Image Quality and Precision of Cine Cardiac MR in Evaluating Left-ventricular Volume and Strain: A Study on Healthy Volunteers.

PURPOSE: To evaluate the effect of model-based deep-learning reconstruction (DLR) compared with that...

Using Deep learning to Predict Cardiovascular Magnetic Resonance Findings from Echocardiography Videos.

BACKGROUND: Echocardiography is the most common modality for assessing cardiac structure and functio...

Not There Yet: Rethinking the Path for Echocardiography Tissue Characterization with Artificial Intelligence.

Fully automated measurement of aortic pulse wave velocity from routine cardiac MRI studies.

INTRODUCTION: Aortic pulse wave velocity (PWV) is a prognostic biomarker for cardiovascular disease,...