Cardiovascular

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

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A Generative Shape Compositional Framework to Synthesize Populations of Virtual Chimeras.

Generating virtual organ populations that capture sufficient variability while remaining plausible i...

The Role of Artificial Intelligence in Cardiology.

Artificial intelligence (AI) has an enormous potential for improving the quality of medical care, di...

Deep Learning-Based Electrocardiogram Model (EIANet) to Predict Emergency Department Cardiac Arrest: Development and External Validation Study.

BACKGROUND: In-hospital cardiac arrest (IHCA) is a severe and sudden medical emergency that is chara...

AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women.

Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction ...

Enhancing atrial fibrillation detection in PPG analysis with sparse labels through contrastive learning.

BACKGROUND: With the advancements in wearable technology, photoplethysmography (PPG) has emerged as ...

Risk factors and an interpretability tool of in-hospital mortality in critically ill patients with acute myocardial infarction.

OBJECTIVE: We aim to develop and validate an interpretable machine-learning model that can provide c...

Investigation of Inter-Patient, Intra-Patient, and Patient-Specific Based Training in Deep Learning for Classification of Heartbeat Arrhythmia.

Effective diagnosis of electrocardiogram (ECG) is one of the simplest and fastest ways to assess the...

A spectral machine learning approach to derive central aortic pressure waveforms from a brachial cuff.

Analyzing cardiac pulse waveforms offers valuable insights into heart health and cardiovascular dise...

Estimation of Machine Learning-Based Models to Predict Dementia Risk in Patients With Atherosclerotic Cardiovascular Diseases: UK Biobank Study.

BACKGROUND: The atherosclerotic cardiovascular disease (ASCVD) is associated with dementia. However,...

An advanced robotic system incorporating haptic feedback for precision cardiac ablation procedures.

This study introduces an innovative master-slave cardiac ablation catheter robot system that employs...

Author name disambiguation based on heterogeneous graph neural network.

With the dramatic increase in the number of published papers and the continuous progress of deep lea...

Machine Learning Predicts Bleeding Risk in Atrial Fibrillation Patients on Direct Oral Anticoagulant.

Predicting major bleeding in nonvalvular atrial fibrillation (AF) patients on direct oral anticoagul...

Deep Learning Approach for Automatic Heartbeat Classification.

Arrhythmia is an irregularity in the rhythm of the heartbeat, and it is the primary method for detec...

Detecting severe coronary artery stenosis in T2DM patients with NAFLD using cardiac fat radiomics-based machine learning.

To analyze radiomics features of cardiac adipose tissue in individuals with type 2 diabetes (T2DM) a...

Urban and rural disparities in stroke prediction using machine learning among Chinese older adults.

Stroke is a significant health concern in China. Differences in stroke risk between rural and urban ...

Identification of lipid metabolism related immune markers in atherosclerosis through machine learning and experimental analysis.

BACKGROUND: Atherosclerosis is a significant contributor to cardiovascular disease, and conventional...

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