Cardiovascular

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

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Enhanced drug classification using machine learning with multiplexed cardiac contractility assays.

Cardiac screening of newly discovered drugs remains a longstanding challenge for the pharmaceutical ...

Application of a Deep Learning-Based Contrast-Boosting Algorithm to Low-Dose Computed Tomography Pulmonary Angiography With Reduced Iodine Load.

OBJECTIVE: The aim of this study was to assess the effectiveness of a deep learning-based image cont...

Generation of a virtual cohort of TAVI patients for in silico trials: a statistical shape and machine learning analysis.

PURPOSE: In silico trials using computational modeling and simulations can complement clinical trial...

Utilizing echocardiography and unsupervised machine learning for heart failure risk identification.

BACKGROUND: Global longitudinal strain (GLS) is recognized as a powerful predictor of heart failure ...

Assessing the impact of ultrasound image standardization in deep learning-based segmentation of carotid plaque types.

BACKGROUND AND OBJECTIVE: Carotid B-mode ultrasound (CBUS) imaging is often used to detect and asses...

Evaluating retinal blood vessels for predicting white matter hyperintensities in ischemic stroke: A deep learning approach.

OBJECTIVE: This study aims to investigate whether a deep learning approach incorporating retinal blo...

Rapid estimation of left ventricular contractility with a physics-informed neural network inverse modeling approach.

Physics-based computer models based on numerical solutions of the governing equations generally cann...

Features selection in a predictive model for cardiac surgery-associated acute kidney injury.

BackgroundCardiac surgery-associated acute kidney injury (CSA-AKI) is related to increased morbidity...

Machine learning-based identification and validation of aging-related genes in cardiomyocytes from patients with atrial fibrillation.

BACKGROUND: Aging is a key risk factor for atrial fibrillation (AF), a prevalent cardiac disorder am...

GloGen: PPG prompts for few-shot transfer learning in blood pressure estimation.

With the rapid advancements in machine learning, its applications in the medical field have garnered...

The role of artificial intelligence in optimizing management of atrial fibrillation in acute ischemic stroke.

Atrial fibrillation (AF) is a severe condition associated with high morbidity and mortality, includi...

Machine learning in the prevention of heart failure.

Heart failure (HF) is a global pandemic with a growing prevalence and is a growing burden on the hea...

Artificial intelligence-enhanced detection of subclinical coronary artery disease in athletes: diagnostic performance and limitations.

PURPOSE: This study evaluates the diagnostic performance of artificial intelligence (AI)-based coron...

Using novel machine learning tools to predict optimal discharge following transcatheter aortic valve replacement.

BACKGROUND: Although transcatheter aortic valve replacement has emerged as an alternative to surgica...

A Pragmatic Approach to Fetal Monitoring via Cardiotocography Using Feature Elimination and Hyperparameter Optimization.

Cardiotocography (CTG) is used to assess the health of the fetus during birth or antenatally in the ...

Coronary artery disease detection using deep learning and ultrahigh-resolution photon-counting coronary CT angiography.

PURPOSE: The purpose of this study was to evaluate the diagnostic performance of automated deep lear...

Effects of end-effector robotic arm reach training with functional electrical stimulation for chronic stroke survivors.

BACKGROUND: Upper-extremity dysfunction significantly affects dependence in the daily lives of strok...

Automated deep learning segmentation of cardiac inflammatory FDG PET.

BACKGROUND: Fluorodeoxyglucose positron emission tomography (FDG PET) with suppression of myocardial...

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