Cardiovascular

A holistic framework for intradialytic hypotension prediction using generative adversarial networks-based data balancing.

BACKGROUND: Intradialytic Hypotension (IDH) is a frequent complication in hemodialysis, yet predicti...

A machine learning model reveals invisible microscopic variation in acute ischaemic stroke (≤ 6 h) with non-contrast computed tomography.

BACKGROUND: In most medical centers, particularly in primary hospitals, non-contrast computed tomogr...

External validation of mortality prediction models in japanese transcatheter aortic valve replacement registry.

OBJECTIVES: Mortality prediction models (MPMs) play a crucial role in risk assessment for transcathe...

Cardiac amyloidosis detection from a single echocardiographic video clip: a novel artificial intelligence-based screening tool.

BACKGROUND AND AIMS: Accurate differentiation of cardiac amyloidosis (CA) from phenotypic mimics rem...

Evolution of CT perfusion software in stroke imaging: from deconvolution to artificial intelligence.

Computed tomography perfusion (CTP) represents one of the main determinants in the decision-making s...

Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients.

BACKGROUND: Hypertension (HTN) is a complex condition with significant heterogeneity in presentation...

Aortic valve leaflet motion for diagnosis and classification of aortic stenosis using single view echocardiography.

BACKGROUND: Accurate classification of aortic stenosis (AS) severity remains challenging despite det...

Inter-AI Agreement in Measuring Cine MRI-Derived Cardiac Function and Motion Patterns: A Pilot Study.

Manually analyzing a series of MRI images to obtain information about the heart's motion is a time-c...

Efficient pretraining of ECG scalogram images using masked autoencoders for cardiovascular disease diagnosis.

Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, emphasizing the need fo...

Design and analysis of TwinCardio framework to detect and monitor cardiovascular diseases using digital twin and deep neural network.

World Health Organization (WHO) estimates 17.9 million deaths globally every year due to Cardiovascu...

Integrating radiomic texture analysis and deep learning for automated myocardial infarction detection in cine-MRI.

Robust differentiation between infarcted and normal myocardial tissue is essential for improving dia...

Enhancing stroke risk prediction through class balancing and data augmentation with CBDA-ResNet50.

Accurate prediction of stroke risk at an early stage is essential for timely intervention and preven...

Improving the Readability of Institutional Heart Failure-Related Patient Education Materials Using GPT-4: Observational Study.

BACKGROUND: Heart failure management involves comprehensive lifestyle modifications such as daily we...

Development and Validation of a Nomogram for Predicting Oral Frailty Risk in Elderly Patients With Ischaemic Stroke.

AIM: To develop and validate a risk prediction model for oral frailty in elderly patients with ischa...

Machine Learning-Based Prognostic Models for Mortality in Patients Receiving Implantable Cardioverter Defibrillators.

BACKGROUND: Accurately predicting the clinical trajectory of patients with implantable cardioverter-...

Artificial intelligence in cardiac sarcoidosis: ECG, Echo, CPET and MRI.

PURPOSE OF REVIEW: Cardiac sarcoidosis is a form of inflammatory cardiomyopathy that varies in its c...

Correction to "Deep Learning Enhanced Near Infrared-II Imaging and Image-Guided Small Interfering Ribonucleic Acid Therapy of Ischemic Stroke".

Artificial intelligence and digital twins for the personalised prediction of hypertension risk.

Hypertension is a significant global health challenge, contributing substantially to morbidity and m...

Current and future applications of robotics in structural heart interventions.

Robotics entered the cardiovascular field in the late 1990s with a robot-assisted coronary artery by...

Automated Laser Modified EndoGraft (ALMEG).

OBJECTIVES: To describe the technical details of a new and innovative method for modifying endograft...

Association of dietary quality, biological aging, progression and mortality of cardiovascular-kidney-metabolic syndrome: insights from mediation and machine learning approaches.

BACKGROUND: To investigate the association between the Dietary Inflammatory Index (DII), biological ...