Deep learning has become the most widely used approach for cardiac image segmentation
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …

Cardiovascular imaging is going to change substantially in the next decade, fueled by the
deep learning revolution. For medical professionals, it is important to keep track of these …

Artificial intelligence (AI) has begun to permeate and reform the field of medicine and
cardiovascular medicine. Impacting about 100 million patients in the United States, the …

Ultrasound is one of the most important examinations for clinical diagnosis of cardiovascular
diseases. The speed of image movements driven by the frequency of the beating heart is …

Accurate segmentation of fetal heart in echocardiography images is essential for detecting
the structural abnormalities such as congenital heart defects (CHDs). Due to the wide …

Induced pluripotent stem cells (iPSC) are one the most prominent innovations of medical
research in the last few decades. iPSCs can be easily generated from human somatic cells …

The evolution of AI and data science has aided in mechanizing several aspects of medical
care requiring critical thinking: diagnosis, risk stratification, and management, thus mitigating …

Background Machine learning (ML) is a powerful tool for identifying and structuring several
informative variables for predictive tasks. Here, we investigated how ML algorithms may …

Artificial intelligence (AI) spring of the past decade created an increased interest into the
topic in business as well as in academia. This resulted in an upward trend in academic …

Background: With the dearth of trained care providers to diagnose congenital heart disease
(CHD) and a surge in machine learning (ML) models, this review aims to estimate the …