Latest AI and machine learning research in cardiovascular for healthcare professionals.
BACKGROUND: Catheter-associated urinary tract infections (CAUTIs) increase clinical burdens. Identif...
PURPOSE OF REVIEW: This opinion paper highlights the advancements in artificial intelligence (AI) te...
Clinical studies have proved significant improvements in hand motor function in stroke patients when...
Timely and precise identification of acute ischemic stroke (AIS) within 4.5Â h is imperative for effe...
RATIONALE AND OBJECTIVES: Hemorrhagic transformation (HT) is one of the most serious complications i...
BACKGROUND: Early and reliable prognostication in post-cardiac arrest patients remains challenging, ...
PURPOSE: To examine the impact of deep learning-augmented contrast enhancement on image quality and ...
BACKGROUND: Multicenter electronic health records can support quality improvement and comparative ef...
PURPOSE: To test the diagnostic performance of an artificial intelligence algorithm for detecting an...
OBJECTIVES: Panoramic radiographs (PRs) can reveal an incidental finding of atherosclerosis, or caro...
BACKGROUND: Atrial fibrillation is associated with an increased risk of cardiovascular hospitalizati...
Intraoperative hypotension prediction has been increasingly emphasized due to its potential clinical...
OBJECTIVES: To compare standard-resolution balanced steady-state free precession (bSSFP) cine images...
Noise detection in ambulatory electrocardiography is investigated as a machine learning binary class...
BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of mortality globally. Environmenta...
BACKGROUND: In recent years, hypertension has been one of the most important noncommunicable disease...
This study aims to use machine learning model to predict laboratory aspirin resistance (AR) in Chine...
Computational models of atrial fibrillation (AF) can help improve success rates of interventions, su...
INTRODUCTION AND OBJECTIVES: Sri Lankans do not have a specific cardiovascular (CV) risk prediction ...
Unsupervised domain adaptation (UDA) has received interest as a means to alleviate the burden of dat...
PURPOSE: To develop an iterative deep learning (DL) reconstruction with spatio-coil regularization a...