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• G
• Ganesan, Prasanth
  Stanford Medicine
• Machine Learning of Electrograms and Clinical Features Predict Acute Termination of Atrial Fibrillation by Ablation
  Prasanth Ganesan
• Principal Component Analysis Identifies Hidden Electrogram Features that Predict Outcomes Atrial Fibrillation Ablation
  Prasanth Ganesan
• Gianni, Carola
  Texas Cardiac Arrhythmia Institute
• Importance of Compression Rate During Left Atrial Appendage Closure with Watchman FLX
  Carola Gianni
• Goergen, Jack
  Northwestern Memorial Hospital
• Modified Atrial Fibrillation Burden: A Novel Metric to Account for Both Rhythm and Rate Control
  Jack Goergen
• Racial Differences in Device-Detected Incident Atrial Fibrillation
  Jack Goergen
• Goswami, Rohan
  Mayo Clinic
• Gender-based stroke risk in patients with afib and heart failure treated with mineralocorticoid antagonists
  Rohan Goswami
• Groh, Christopher
  University of Utah School of Medicine
• Increased Delay from Atrial Fibrillation Diagnosis to Ablation Increases Mortality in Structural Heart Disease Patients
  Christopher Groh