Cardiovascular

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

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Identifying abdominal aortic aneurysm size and presence using Natural Language Processing of radiology reports: a systematic review and meta-analysis.

BACKGROUND AND AIM: Prior investigations of the natural history of abdominal aortic aneurysms (AAAs)...

Machine learning to detect recent recreational drug use in intensive cardiac care units.

BACKGROUND: Although recreational drug use is a strong risk factor for acute cardiovascular events, ...

Machine Learning Analysis of Nutrient Associations with Peripheral Arterial Disease: Insights from NHANES 1999-2004.

BACKGROUND: Peripheral arterial disease (PAD) is a common manifestation of atherosclerosis, affectin...

A deep learning model for QRS delineation in organized rhythms during in-hospital cardiac arrest.

BACKGROUND: Cardiac arrest (CA) is the sudden cessation of heart function, typically resulting in lo...

Neural-symbolic hybrid model for myosin complex in cardiac ventriculum decodes structural bases for inheritable heart disease from its genetic encoding.

BACKGROUND: Human ventriculum myosin (βmys) powers contraction sometimes in complex with myosin bind...

Improving myocardial infarction diagnosis with Siamese network-based ECG analysis.

BACKGROUND: Heart muscle damage from myocardial infarction (MI) is brought on by insufficient blood ...

Segmentation of coronary artery and calcification using prior knowledge based deep learning framework.

BACKGROUND: Computed tomography angiography (CTA) is used to screen for coronary artery calcificatio...

Enhancing quantitative coronary angiography (QCA) with advanced artificial intelligence: comparison with manual QCA and visual estimation.

Artificial intelligence-based quantitative coronary angiography (AI-QCA) was introduced to address m...

Application of three-dimensional printing in the planning and execution of aortic aneurysm repair.

INTRODUCTION: The accuracy of fenestrations in stent grafts for complex aortic aneurysms and dissect...

The impact of architectural modifications on relative resistance to fluid flow in ventricular catheters.

INTRODUCTION: Although many ventricular catheter designs exist for hydrocephalus treatment, few stan...

Machine learning to predict stroke risk from routine hospital data: A systematic review.

PURPOSE: Stroke remains a leading cause of morbidity and mortality. Despite this, current risk strat...

Human-centred AI for emergency cardiac care: Evaluating RAPIDx AI with PROLIFERATE_AI.

BACKGROUND: Chest pain diagnosis in emergency care is hindered by overlapping cardiac and non-cardia...

Predictive models of clinical outcome of endovascular treatment for anterior circulation stroke using machine learning.

BACKGROUND AND PURPOSE: Mechanical Thrombectomy (MT) has recently become the standard of care for an...

Semi-supervised Strong-Teacher Consistency Learning for few-shot cardiac MRI image segmentation.

BACKGROUND AND OBJECTIVE: Cardiovascular disease is a leading cause of mortality worldwide. Automate...

Using artificial intelligence to evaluate adherence to best practices in one anastomosis gastric bypass: first steps in a real-world setting.

BACKGROUND: Safety in one anastomosis gastric bypass (OAGB) is judged by outcomes, but it seems reas...

Optimizing stroke prediction using gated recurrent unit and feature selection in Sub-Saharan Africa.

BACKGROUND: Stroke remains a leading cause of death and disability worldwide, with African populatio...

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