Cardiovascular

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

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Development and validation of machine learning-based prediction model for outcome of cardiac arrest in intensive care units.

Cardiac arrest (CA) poses a significant global health challenge and often results in poor prognosis....

A brief history and clinical use of robotic procedures in the cardiovascular system.

Robotic-assisted percutaneous coronary intervention (r-PCI) exemplifies the advancement of intervent...

Compliance Evaluation with ChatGPT for Diagnosis and Treatment in Patients Brought to the ED with a Preliminary Diagnosis of Stroke.

OBJECTIVES: Chat Generative Pre-trained Transformer (ChatGPT) is a natural language processing produ...

Design of a Soft Robotic Artificial Cardiac Wall.

BACKGROUND: In cardiovascular engineering, the recent introduction of soft robotic technologies shed...

Super-resolution deep learning reconstruction for improved quality of myocardial CT late enhancement.

PURPOSE: Myocardial computed tomography (CT) late enhancement (LE) allows assessment of myocardial s...

Advancing Sports Cardiology: Integrating Artificial Intelligence with Wearable Devices for Cardiovascular Health Management.

Sports cardiology focuses on athletes' cardiovascular health, yet sudden cardiac death remains a sig...

Liquid-bodied antibiofilm robot with switchable viscoelastic response for biofilm eradication on complex surface topographies.

Recalcitrant biofilm infections pose a great challenge to human health. Micro- and nanorobots have b...

Development and validation of machine learning models for predicting extubation failure in patients undergoing cardiac surgery: a retrospective study.

Patients with multiple comorbidities and those undergoing complex cardiac surgery may experience ext...

Machine learning analysis of integrated ABP and PPG signals towards early detection of coronary artery disease.

Every year, Coronary Artery Disease (CAD) claims lives of over a million people. CAD occurs when the...

Patient Perspectives on Conversational Artificial Intelligence for Atrial Fibrillation Self-Management: Qualitative Analysis.

BACKGROUND: Conversational artificial intelligence (AI) allows for engaging interactions, however, i...

Deep learning based automatic quantification of aortic valve calcification on contrast enhanced coronary CT angiography.

Quantifying aortic valve calcification is critical for assessing the severity of aortic stenosis, pr...

A Novel Explainable Attention-Based Meta-Learning Framework for Imbalanced Brain Stroke Prediction.

The accurate prediction of brain stroke is critical for effective diagnosis and management, yet the ...

Low-dose CT reconstruction using cross-domain deep learning with domain transfer module.

. X-ray computed tomography employing low-dose x-ray source is actively researched to reduce radiati...

Prediction of Hypertension in the Pediatric Population Using Machine Learning and Transfer Learning: A Multicentric Analysis of the SAYCARE Study.

OBJECTIVE: To develop a machine learning (ML) model utilizing transfer learning (TL) techniques to p...

Early prediction of cardiovascular events following treatments in female breast cancer patients: Application of real-world data and artificial intelligence.

• Application of real-world data and artificial intelligence in detecting cardiotoxicity following c...

Post-Bariatric Hypoglycemia After Gastric Bypass: Clinical Characteristics, Risk Factors, and Future Directions-A Response to Grover et al.

BACKGROUND: Post-bariatric hypoglycemia (PBH) after Roux-en-Y gastric bypass (RYGB) is a complex com...

Application of Machine Learning for Patients With Cardiac Arrest: Systematic Review and Meta-Analysis.

BACKGROUND: Currently, there is a lack of effective early assessment tools for predicting the onset ...

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