Using machine learning to predict early readmission following esophagectomy.

Journal: The Journal of thoracic and cardiovascular surgery
Published Date: May 29, 2020

Abstract

OBJECTIVE: To establish a machine learning (ML)-based prediction model for readmission within 30 days (early readmission or early readmission) of patients based on their profile at index hospitalization for esophagectomy.

Authors

  • Siavash Bolourani
    Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Northwell Health, Hempstead, NY, USA.
  • Mohammad A Tayebi
    School of Computing Science, Simon Fraser University, Burnaby, British Columbia, Canada.
  • Li Diao
    The Feinstein Institutes for Medical Research, Manhasset, NY.
  • Ping Wang
    School of Chemistry and Chemical Engineering, Shandong University of Technology, 255049, Zibo, PR China. Electronic address: wangping876@163.com.
  • Vihas Patel
    Department of Surgery, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY.
  • Frank Manetta
    Department of Cardiovascular and Thoracic Surgery, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY.
  • Paul C Lee
    Department of Cardiovascular and Thoracic Surgery, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY. Electronic address: plee15@northwell.edu.

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