AI Medical Compendium Journal:
JACC. Cardiovascular imaging

Showing 21 to 30 of 83 articles

Current Applications of Robot-Assisted Ultrasound Examination.

JACC. Cardiovascular imaging
Despite advances in miniaturization and automation, the need for expert acquisition of a full echocardiogram, including Doppler, has restricted access in remote areas. Recent developments in robotics, teleoperation, and upgraded telecommunications in...

Direct Risk Assessment From Myocardial Perfusion Imaging Using Explainable Deep Learning.

JACC. Cardiovascular imaging
BACKGROUND: Myocardial perfusion imaging (MPI) is frequently used to provide risk stratification, but methods to improve the accuracy of these predictions are needed.

Deep Learning of Coronary Calcium Scores From PET/CT Attenuation Maps Accurately Predicts Adverse Cardiovascular Events.

JACC. Cardiovascular imaging
BACKGROUND: Assessment of coronary artery calcium (CAC) by computed tomographic (CT) imaging provides an accurate measure of atherosclerotic burden. CAC is also visible in computed tomographic attenuation correction (CTAC) scans, always acquired with...

Using Deep-Learning Algorithms to Simultaneously Identify Right and Left Ventricular Dysfunction From the Electrocardiogram.

JACC. Cardiovascular imaging
OBJECTIVES: This study sought to develop DL models capable of comprehensively quantifying left and right ventricular dysfunction from ECG data in a large, diverse population.