OBJECTIVE: The study evaluates the relationship of coronary stenosis, atherosclerotic plaque characteristics (APCs) and age using artificial intelligence enabled quantitative coronary computed tomographic angiography (AI-QCT).
To investigate the image quality of coronary CT angiography (CCTA) subjected to deep learning-based reconstruction algorithm (DLR) method and its diagnostic performance for stenosis caused by coronary calcified lesions. We enrolled 33 consecutive p...
EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
May 17, 2021
EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
May 17, 2021
BACKGROUND: It would be ideal for a non-hyperaemic index to predict fractional flow reserve (FFR) more accurately, given FFR's extensive validation in a multitude of clinical settings.
EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
May 17, 2021
BACKGROUND: In recent years, the use of deep learning has become more commonplace in the biomedical field and its development will greatly assist clinical and imaging data interpretation. Most existing machine learning methods for coronary angiograph...
AIMS: Facial features were associated with increased risk of coronary artery disease (CAD). We developed and validated a deep learning algorithm for detecting CAD based on facial photos.
BACKGROUND: Noninvasive imaging modalities are of central importance in the diagnosis of chronic coronary syndrome (CCS) in the current guidelines of the European Society of Cardiology (ESC), while the role of primary invasive coronary angiography in...
AIMS: Our aim was to evaluate the performance of machine learning (ML), integrating clinical parameters with coronary artery calcium (CAC), and automated epicardial adipose tissue (EAT) quantification, for the prediction of long-term risk of myocardi...
During the latest years, artificial intelligence, and especially machine learning (ML), have experienced a growth in popularity due to their versatility and potential in solving complex problems. In fact, ML allows the efficient handling of big volum...
PURPOSE: The purpose of this study was to evaluate the accuracy of a novel fully automated deep learning (DL) algorithm implementing a recurrent neural network (RNN) with long short-term memory (LSTM) for the detection of coronary artery calcium (CAC...
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