Cardiovascular

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

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Explainable artificial intelligence for stroke prediction through comparison of deep learning and machine learning models.

Failure to predict stroke promptly may lead to delayed treatment, causing severe consequences like p...

Novel anoikis-related diagnostic biomarkers for aortic dissection based on machine learning.

Aortic dissection (AD) is one of the most dangerous diseases of the cardiovascular system, which is ...

Predicting host health status through an integrated machine learning framework: insights from healthy gut microbiome aging trajectory.

The gut microbiome, recognized as a critical component in the development of chronic diseases and ag...

Integrating EPSOSA-BP neural network algorithm for enhanced accuracy and robustness in optimizing coronary artery disease prediction.

Coronary artery disease represents a formidable health threat to middle-aged and elderly populations...

Predictive modelling of hospital-acquired infection in acute ischemic stroke using machine learning.

Hospital-acquired infections (HAIs) are serious complication for patients with acute ischemic stroke...

Multi-Energy Evaluation of Image Quality in Spectral CT Pulmonary Angiography Using Different Strength Deep Learning Spectral Reconstructions.

RATIONALE AND OBJECTIVES: To evaluate and compare image quality of different energy levels of virtua...

Development of a Self-Deploying Extra-Aortic Compression Device for Medium-Term Hemodynamic Stabilization: A Feasibility Study.

Hemodynamic stabilization is crucial in managing acute cardiac events, where compromised blood flow ...

Comparative Algorithms for Identifying and Counting Hospitalisation Episodes of Care for Coronary Heart Disease Using Administrative Data.

PURPOSE: Measures of disease burden using hospital administrative data are susceptible to over-infla...

Predicting lack of clinical improvement following varicose vein ablation using machine learning.

OBJECTIVE: Varicose vein ablation is generally indicated in patients with active/healed venous ulcer...

Predicting the likelihood of readmission in patients with ischemic stroke: An explainable machine learning approach using common data model data.

BACKGROUND: Ischemic stroke affects 15 million people worldwide, causing five million deaths annuall...

Diagnosis of intracranial aneurysms by computed tomography angiography using deep learning-based detection and segmentation.

BACKGROUND: Detecting and segmenting intracranial aneurysms (IAs) from angiographic images is a labo...

Effect of artificial intelligence-based video-game system on dysphagia in patients with stroke: A randomized controlled trial.

BACKGROUND AND AIMS: Post-stroke dysphagia is highly prevalent and causes complication. While video ...

A wrapper method for finding optimal subset of multimodal Magnetic Resonance Imaging sequences for ischemic stroke lesion segmentation.

Multimodal data, while being information-rich, contains complementary as well as redundant informati...

12 lead surface ECGs as a surrogate of atrial electrical remodeling - a deep learning based approach.

BACKGROUND AND PURPOSE: Atrial fibrillation (AF), a common arrhythmia, is linked with atrial electri...

Screening prediction models using artificial intelligence for moderate-to-severe obstructive sleep apnea in patients with acute ischemic stroke.

BACKGROUND: Obstructive sleep apnea (OSA) is common after stroke. Still, routine screening of OSA wi...

Predicting the risk of cardiovascular disease in adults exposed to heavy metals: Interpretable machine learning.

Machine learning exhibits excellent performance in terms of predictive power. We aimed to construct ...

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