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...
Coronary computed tomography angiography (cCTA) is a reliable and clinically proven method for the evaluation of coronary artery disease. cCTA data sets can be used to derive fractional flow reserve (FFR) as CT-FFR. This method has respectable result...
AIMS: Symptom-based pretest probability scores that estimate the likelihood of obstructive coronary artery disease (CAD) in stable chest pain have moderate accuracy. We sought to develop a machine learning (ML) model, utilizing clinical factors and t...
We developed machine learning methods to identify fibrolipidic and fibrocalcific A-lines in intravascular optical coherence tomography (IVOCT) images using a comprehensive set of handcrafted features. We incorporated features developed in previous st...
Automatic and accurate segmentation of intravascular optical coherence tomography imagery is of great importance in computer-aided diagnosis and in treatment of cardiovascular diseases. However, this task has not been well addressed for two reasons. ...
Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML), which is a subset of AI wherein machines autonomously acquire information by extracting patterns from large databases, has been increasingly used within th...
Journal of the American Heart Association
Feb 19, 2019
Background An angiography-based supervised machine learning ( ML ) algorithm was developed to classify lesions as having fractional flow reserve ≤0.80 versus >0.80. Methods and Results With a 4:1 ratio, 1501 patients with 1501 intermediate lesions we...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
Coronary artery lumen delineation, to localize and grade stenosis, is an important but tedious and challenging task for coronary heart disease evaluation. Deep learning has recently been successful applied to many applications, including medical imag...
BACKGROUND: Coronary computed tomographic angiography (CTA) is a reliable modality to detect coronary artery disease. However, CTA generally overestimates stenosis severity compared with invasive angiography, and angiographic stenosis does not necess...
Heavy smokers undergoing screening with low-dose chest CT are affected by cardiovascular disease as much as by lung cancer. Low-dose chest CT scans acquired in screening enable quantification of atherosclerotic calcifications and thus enable identifi...
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