Year: 2024
Type: editorial
Abstract: Sudden cardiac death (SCD) from ventricular tachycardia (VT) and ventricular fibrillation and other cardiac arrhythmias including atrial fibrillation (AF) and bradyarrhythmias collectively affect millions of patients worldwide and are significant causes of global morbidity and mortality.There has been a stagnation in translating bench-to-bedside innovations to break-throughs leading to improved patient outcomes.Similar concerns have been raised in other disciplines.1,2 Furthermore, there has been a significant erosion in the number of research-focused heart rhythm investigators, particularly in basic and translational
Institutions: Stanford University, New York University, University of Wisconsin–Madison, Cleveland Clinic, Cleveland Clinic Research, Washington University in St. Louis, Cooper Medical School of Rowan University, Cedars-Sinai Medical Center, University of California, Los Angeles, Cedars-Sinai Smidt Heart Institute
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
Awards: G3541864657, The Dynamics of Human Atrial Fibrillation, RADIOMIC APPROACHES TO IMPROVE TARGETING FOR ATRIAL FIBRILLATION CATHETER ABLATION, Machine Learning in Atrial Fibrillation, Computational Medicine in the Heart, Integrated Training Program, Atrial Fibrillation Post-GWAS: Mechanisms to Treatment, Machine Learning for Ventricular Arrhythmias
OpenAlex ID: W4400891308