Explainable Machine Learning Model to Preoperatively Predict Postoperative Complications in Inpatients With Cancer Undergoing Major Operations.

Abstract

Authors

• Matthew C Hernandez
  Department of Surgery, University of New Mexico, Albuquerque, NM.
• Chen Chen
  The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
• Andrew Nguyen
  2Department of Neurosurgery, UC San Diego School of Medicine, San Diego.
• Kevin Choong
  Department of Surgery, Division of Oncology, Primas Health, University of South Carolina Medical School, Greeneville, SC.
• Cameron Carlin
  The Laura P. and Leland K. Whittier Virtual Pediatric Intensive Care Unit, Children's Hospital Los Angeles, 4650 Sunset Blvd, Los Angeles, CA 90027, United States. Electronic address: cameronscarlin@gmail.com.
• Rebecca A Nelson
  Department of Computational and Quantitative Medicine, Division of Biostatistics, City of Hope National Medical Center, Duarte, CA.
• Lorenzo A Rossi
  Applied AI and Data Science Department, City of Hope National Medical Center, Duarte, California, USA.
• Naini Seth
  Department of Clinical Informatics, City of Hope National Medical Center, Duarte, CA.
• Kathy McNeese
  Department of Surgery, University of New Mexico, Albuquerque, NM.
• Bertram Yuh
  City of Hope National Medical Center, Duarte, California.
• Zahra Eftekhari
  City of Hope National Medical Center, Duarte, California.
• Lily L Lai
  Department of Surgery, University of New Mexico, Albuquerque, NM.

Keywords

External Resources