Cardiovascular

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

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Predicting cardiovascular disease in patients with mental illness using machine learning.

BACKGROUND: Cardiovascular disease (CVD) is twice as prevalent among individuals with mental illness...

A Comprehensive Review of Artificial Intelligence (AI) Applications in Pulmonary Hypertension (PH).

Pulmonary hypertension (PH) is a complex condition associated with significant morbidity and mortal...

DCTP-Net: Dual-Branch CLIP-Enhance Textual Prompt-Aware Network for Acute Ischemic Stroke Lesion Segmentation From CT Image.

Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing di...

FDDSeg: Unleashing the Power of Scribble Annotation for Cardiac MRI Images Through Feature Decomposition Distillation.

Cardiovascular diseases can be diagnosed with computer assistance when using the magnetic resonance ...

Machine learning and statistical shape modelling for real-time prediction of stent deployment in realistic anatomies.

The rise in minimally invasive procedures has created a demand for efficient and reliable planning s...

Artificial Intelligence-Enabled Novel Atrial Fibrillation Diagnosis System Using 3D Pulse Perception Flexible Pressure Sensor Array.

Atrial fibrillation (AF) as one of the most common cardiovascular diseases has attracted great atten...

Machine learning derivation of two cardiac arrest subphenotypes with distinct responses to treatment.

INTRODUCTION: Cardiac arrest (CA), characterized by its heterogeneity, poses challenges in patient m...

A novel RFE-GRU model for diabetes classification using PIMA Indian dataset.

Diabetes is a long-term condition characterized by elevated blood sugar levels. It can lead to a var...

Using deep learning to shorten the acquisition time of brain MRI in acute ischemic stroke: Synthetic T2W images generated from b0 images.

OBJECTIVE: This study aimed to assess the feasibility of the deep learning in generating T2 weighted...

Deep learning in 3D cardiac reconstruction: a systematic review of methodologies and dataset.

This study presents an advanced methodology for 3D heart reconstruction using a combination of deep ...

Unlocking the diagnostic potential of electrocardiograms through information transfer from cardiac magnetic resonance imaging.

Cardiovascular diseases (CVD) can be diagnosed using various diagnostic modalities. The electrocardi...

Machine learning-based interpretation of non-contrast feature tracking strain analysis and T1/T2 mapping for assessing myocardial viability.

Assessing myocardial viability is crucial for managing ischemic heart disease. While late gadolinium...

Forecasting cardiovascular disease mortality using artificial neural networks in Sindh, Pakistan.

Cardiovascular disease (CVD) is a leading cause of death and disability worldwide, and its incidence...

ECGEFNet: A two-branch deep learning model for calculating left ventricular ejection fraction using electrocardiogram.

Left ventricular systolic dysfunction (LVSD) and its severity are correlated with the prognosis of c...

Effectiveness of robot-assisted task-oriented training intervention for upper limb and daily living skills in stroke patients: A meta-analysis.

PURPOSE: Stroke is one of the leading causes of acquired disability in adults in high-income countri...

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