Results 131 to 140 of about 120,013 (263)
Severe Hypokalemia and Life-Threatening Ventricular Arrhythmias: A Case of Normotensive Primary Aldosteronism. [PDF]
Daniel HN, Belleus V, Wang J, Adjovu S.
europepmc +1 more source
ABSTRACT The Nav1.5 channel, a major isoform of voltage‐gated sodium ion channel, is mainly found in ventricular cardiomyocytes, playing a key role in generating essential cardiac action potentials for normal heart rhythms. Mutations in Nav1.5 have been associated with severe heart conditions such as long QT syndrome, Brugada syndrome, cardiac ...
Arkapravo Chattopadhyay +3 more
wiley +1 more source
A new approach methodology for studying intrinsic ventricular arrhythmias in Fabry disease. [PDF]
Monteiro da Rocha A +6 more
europepmc +1 more source
“Two‐For‐One”: 4D Cardiac and Pulmonary MR Imaging From a Single Acquisition Using bSTAR
ABSTRACT Purpose To generate 4D (3D+time) images of both the heart and lungs using a single volumetric radial free‐breathing bSSFP dual echo acquisition (bSTAR) with two image reconstructions within a single pipeline deployed inline at 0.55 and 1.5 T.
Pierre Daudé +9 more
wiley +1 more source
Treatment of ventricular arrhythmias with oral sotalol in four horses. [PDF]
Junge HK +3 more
europepmc +1 more source
ABSTRACT Purpose To develop a unified image reconstruction framework that bridges real‐time and gated cardiac MRI, including quantitative MRI. Methods We introduce generative multitasking, which learns subject‐ and dataset‐specific implicit neural temporal bases from sequence timings and an interpretable latent space for cardiac and respiratory motion.
Xinguo Fang, Anthony G. Christodoulou
wiley +1 more source
Arrhythmias from the Right Ventricular Moderator Band: Diagnosis and Management
Megan Barber, Jason Chinitz, Roy John
doaj +1 more source
Modes of onset of ventricular arrhythmias in J-wave syndromes: mechanistic insights from computational modeling. [PDF]
Zhang Z, Qu Z.
europepmc +1 more source
Training Deep Learning Based Dynamic MR Image Reconstruction Using Synthetic Fractals
ABSTRACT Purpose To investigate whether synthetically generated fractal data can be used to train deep learning (DL) models for dynamic MRI reconstruction, thereby avoiding the privacy, licensing, and availability limitations associated with cardiac MR training datasets.
Anirudh Raman +10 more
wiley +1 more source

