OBJECTIVE: Cardiovascular disease (CVD) is a major healthcare challenge and therefore early risk assessment is vital. Previous assessment techniques use either "conventional CVD risk calculators (CCVRC)" or machine learning (ML) paradigms. These tech...
IEEE journal of biomedical and health informatics
Aug 11, 2022
Automatic coronary artery segmentation is of great value in diagnosing coronary disease. In this paper, we propose an automatic coronary artery segmentation method for coronary computerized tomography angiography (CCTA) images based on a deep convolu...
OBJECTIVE: The exploration and the implementation of a deep learning method using a state-of-the-art convolutional neural network for the classification of polar maps represent myocardial perfusion for the detection of coronary artery disease.
Computer methods and programs in biomedicine
Jun 21, 2022
BACKGROUND AND OBJECTIVE: Incomplete Kawasaki disease (KD) has often been misdiagnosed due to a lack of the clinical manifestations of classic KD. However, it is associated with a markedly higher prevalence of coronary artery lesions. Identifying cor...
IEEE/ACM transactions on computational biology and bioinformatics
Jun 3, 2022
Machine Learning (ML) approaches are increasingly being used in biomedical applications. Important challenges of ML include choosing the right algorithm and tuning the parameters for optimal performance. Automated ML (AutoML) methods, such as Tree-ba...
PURPOSE OF REVIEW: Robotics has been used in multiple areas of procedural medical intervention. Robotic percutaneous coronary intervention (PCI) has been available since 2004. Its adoption has been slow with initial application in simple cases.
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