An Open-Architecture AI Model for CPT Coding in Breast Surgery: Development, Validation, and Prospective Testing.

Journal: Annals of surgery
Published Date:

Abstract

OBJECTIVE: To develop, validate, and prospectively test an open-architecture, transformer-based Artificial Intelligence (AI) model to extract procedure codes from free-text breast surgery operative notes.

Authors

  • Mohamad El Moheb
    Division of Trauma, Emergency Surgery, and Surgical Critical Care, Massachusetts General Hospital, Boston, Massachusetts.
  • Kristin Putman
    From the University of Maryland Medical Intelligent Imaging (UM2ii) Center, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 670 W Baltimore St, First Floor, Room 1172, Baltimore, MD 21201.
  • Olivia Sears
    Department of Surgery, University of Virginia, Charlottesville, VA.
  • Melina R Kibbe
    Department of Surgery, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • K Craig Kent
    Department of Surgery, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • David R Brenin
    Department of Surgery, University of Virginia School of Medicine, Charlottesville, VA, USA.
  • Allan Tsung
    Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA tsunga@upmc.edu.

Keywords

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