Clinical & Experimental Cardiology
Open Access

Department of Cardiology, Cardiovascular Institute, Stanford University School of Medicine, Stanford, USA

Publications

• Mini Review   
  Advances in Electrocardiogram-Based Artificial Intelligence Reveal Multisystem Biomarkers
  Author(s): Xichong Liu, Sabyasachi Bandyopadhyay and Albert J. Rogers*
  
  As Artificial Intelligence (AI) plays an increasingly prominent role in society, its application in clinical cardiology is gaining traction by providing innovative diagnostic, prognostic, and therapeutic solutions. Electrocardiogram (ECG), as a ubiquitous diagnostic tool in cardiology, has emerged as the leading data source for Deep Learning (DL) applications. A recent study from our group used ECG-based DL model to identify cardiac wall motion abnormalities and outperformed expert human interpretation. Motivated by this work and that of many others, we aim to discuss advances, limitations, future directions, and equity considerations in DL models for ECG-based AI applications... View More»
  DOI: 10.35248/2155-9880.25.16.935

  Abstract HTML PDF