Deep Learning Model of Diastolic Dysfunction Risk Stratifies the Progression of Early-Stage Aortic Stenosis.

Abstract

Authors

• Márton Tokodi
  Division of Cardiology, West Virginia University Heart & Vascular Institute, Morgantown, West Virginia.
• Rohan Shah
  Rutgers University School of Medicine, Newark, New Jersey.
• Ankush Jamthikar
  Department of Electronics and Communication Engineering, Visvesvaraya National Institute of Technology, Nagpur, Maharashtra, India.
• Neil Craig
  Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom.
• Yasmin Hamirani
  Division of Cardiovascular Diseases and Hypertension, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA.
• Grace Casaclang-Verzosa
  Division of Cardiology, West Virginia University Heart & Vascular Institute, Morgantown, West Virginia.
• Rebecca T Hahn
  Seymour, Paul, and Gloria Milstein Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center and NewYork-Presbyterian Hospital, New York, New York, USA.
• Marc R Dweck
  British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Chancellor's Building, 49 Little France Cres, Edinburgh, UK.
• Philippe Pibarot
  Québec Department of Medicine, Heart and Lung Institute, Laval University, Québec City, Québec, Canada.
• Naveena Yanamala
  1 Exposure Assessment Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Morgantown, West Virginia, USA.
• Partho P Sengupta
  Division of Cardiovascular Diseases and Hypertension, Robert Wood Johnson University Hospital, and Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA.

Keywords

External Resources