Artificial intelligence prediction model for readmission after DIEP flap breast reconstruction based on NSQIP data.

Journal: Journal of plastic, reconstructive & aesthetic surgery : JPRAS
Published Date: Apr 20, 2025

Abstract

BACKGROUND: Readmissions following deep inferior epigastric perforator (DIEP) flap breast reconstruction represent a significant healthcare burden, yet current risk prediction methods lack precision in identifying high-risk patients. We developed a machine learning model to predict 30-day readmission risk using a large national surgical quality database.

Authors

  • Berk B Ozmen
    Department of Plastic Surgery, Cleveland Clinic, Cleveland, OH, USA.
  • Diwakar Phuyal
    Department of Plastic Surgery, Cleveland Clinic, Cleveland, OH, USA.
  • Ibrahim Berber
    Department of Computer and Data Sciences, Case School of Engineering, Case Western Reserve University, Cleveland, OH, USA.
  • Graham S Schwarz
    Department of Plastic Surgery, Cleveland Clinic, Cleveland, OH, USA.

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