Adverse Outcomes Prediction for Congenital Heart Surgery: A Machine Learning Approach.

Journal: World journal for pediatric & congenital heart surgery
Published Date: Apr 28, 2021

Abstract

OBJECTIVE: Risk assessment tools typically used in congenital heart surgery (CHS) assume that various possible risk factors interact in a linear and additive fashion, an assumption that may not reflect reality. Using artificial intelligence techniques, we sought to develop nonlinear models for predicting outcomes in CHS.

Authors

  • Dimitris Bertsimas
    Dimitris Bertsimas, Jack Dunn, Colin Pawlowski, John Silberholz, Alexander Weinstein, and Ying Daisy Zhuo, Massachusetts Institute of Technology, Cambridge; Eddy Chen, Massachusetts General Hospital Cancer Center; Harvard Medical School; Aymen A. Elfiky, Dana-Farber Cancer Institute; Brigham and Women's Hospital; Harvard Medical School, Boston, MA.
  • Daisy Zhuo
    Interpretable AI, Boston, Massachusetts.
  • Jack Dunn
    Dimitris Bertsimas, Jack Dunn, Colin Pawlowski, John Silberholz, Alexander Weinstein, and Ying Daisy Zhuo, Massachusetts Institute of Technology, Cambridge; Eddy Chen, Massachusetts General Hospital Cancer Center; Harvard Medical School; Aymen A. Elfiky, Dana-Farber Cancer Institute; Brigham and Women's Hospital; Harvard Medical School, Boston, MA.
  • Jordan Levine
    Interpretable AI, Boston, MA.
  • Eugenio Zuccarelli
    Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA; Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Nikos Smyrnakis
    Operations Research Center, 2167Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Zdzislaw Tobota
    Department for Pediatric Cardiothoracic Surgery, 49805Children's Memorial Health Institute, Warsaw, Poland.
  • Bohdan Maruszewski
    Department for Pediatric Cardiothoracic Surgery, 49805Children's Memorial Health Institute, Warsaw, Poland.
  • Jose Fragata
    Hospital de Santa Marta and NOVA University, Lisbon, Portugal.
  • George E Sarris
    Athens Heart Surgery Institute, Greece.

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