Ensemble machine learning for the prediction of patient-level outcomes following thyroidectomy.

Journal: American journal of surgery
Published Date: Dec 3, 2020

Abstract

BACKGROUND: Accurate prediction of thyroidectomy complications is necessary to inform treatment decisions. Ensemble machine learning provides one approach to improve prediction.

Authors

  • Carolyn D Seib
    Stanford-Surgery Policy Improvement Research and Education Center (S-SPIRE), Department of Surgery, Stanford University School of Medicine, Stanford, CA, United States; Division of General Surgery, Palo Alto Veterans Affairs Health Care System, United States. Electronic address: cseib@stanford.edu.
  • James P Roose
    University of California, Berkeley, Division of Biostatistics, Berkeley, United States.
  • Alan E Hubbard
  • Insoo Suh
    University of California, San Francisco, Section of Endocrine Surgery, San Francisco, United States.

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