Invasive angiography is the reference standard for coronary artery disease (CAD) diagnosis
but is expensive and associated with certain risks. Machine learning (ML) using clinical and …

The development of medical science greatly depends on the increased utilization of
machine learning algorithms. By incorporating machine learning, the medical imaging field …

While supervised learning techniques have demonstrated state-of-the-art performance in
many medical image analysis tasks, the role of sample selection is important. Selecting the …

Coronary arteriongraphy (CAG) is an accurate invasive technique for the diagnosis of
coronary heart disease (CHD). However, its invasive procedure is not appropriate for the …

Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and often
leads to a heart attack. It annually causes millions of deaths and billions of dollars in …

Active Learning has been a popular method to circumvent the labeling cost in machine
learning methods. The majority of active learning approaches can be classified into two …

Background and objective Cardiovascular diseases are an extremely widespread sickness
and account for 17 million deaths in the world per annum. Coronary artery disease (CAD) is …

Active learning (AL) methods create an optimized labeled training set from unlabeled data.
We introduce a novel online active deep learning method for medical image analysis. We …

Introduction Multiple trials have demonstrated broad performance ranges for tests attempting
to detect coronary artery disease. The most common test, SPECT, requires capital-intensive …

Aim: The development of coronary artery disease (CAD), a highly prevalent disease
worldwide, is influenced by several modifiable risk factors. Predictive models built using …