Prediction of coronary artery bypass graft outcomes using a single surgical note: An artificial intelligence-based prediction model study.

Journal: PloS one
Published Date: Apr 25, 2024

Abstract

BACKGROUND: Healthcare providers currently calculate risk of the composite outcome of morbidity or mortality associated with a coronary artery bypass grafting (CABG) surgery through manual input of variables into a logistic regression-based risk calculator. This study indicates that automated artificial intelligence (AI)-based techniques can instead calculate risk. Specifically, we present novel numerical embedding techniques that enable NLP (natural language processing) models to achieve higher performance than the risk calculator using a single preoperative surgical note.

Authors

  • John Del Gaizo
    Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC, USA.
  • Curry Sherard
    College of Medicine, Medical University of South Carolina, Charleston, South Carolina, United States of America.
  • Khaled Shorbaji
    Division of Cardiothoracic Surgery, Department of Surgery, Medical University of South Carolina, Charleston, South Carolina, United States of America.
  • Brett Welch
    Division of Cardiothoracic Surgery, Department of Surgery, Medical University of South Carolina, Charleston, South Carolina, United States of America.
  • Roshan Mathi
    Division of Cardiothoracic Surgery, Department of Surgery, Medical University of South Carolina, Charleston, South Carolina, United States of America.
  • Arman Kilic
    Division of Cardiac Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania. Electronic address: kilica2@upmc.edu.

Keywords

External Resources

Popular Topics
Recent Journals