Abstract Machine learning analysis of biomedical images has seen significant recent
advances. In contrast, there has been much less work on medical videos, despite the fact …

Echocardiography is the commonest medical ultrasound examination, but automated
interpretation is challenging and hinges on correct recognition of the 'view'(imaging plane …

Learning spatiotemporal features is an important task for efficient video understanding
especially in medical images such as echocardiograms. Convolutional neural networks …

Accurate assessment of cardiac function is crucial for the diagnosis of cardiovascular
disease, screening for cardiotoxicity and decisions regarding the clinical management of …

This study extends the state of the art of deep learning convolutional neural network (CNN)
to the classification of video images of echocardiography, aiming at assisting clinicians in …

Background Laboratory testing is routinely used to assay blood biomarkers to provide
information on physiologic state beyond what clinicians can evaluate from interpreting …

Echocardiography is essential to cardiology. However, the need for human interpretation
has limited echocardiography's full potential for precision medicine. Deep learning is an …

Despite progressive improvements over the decades, the rich temporally resolved data in an
echocardiogram remain underutilized. Human assessments reduce the complex patterns of …

Echocardiography uses ultrasound technology to capture high temporal and spatial
resolution images of the heart and surrounding structures, and is the most common imaging …

Deep learning and computer vision algorithms can deliver highly accurate and automated
interpretation of medical imaging to augment and assist clinicians. However, medical …