Machine Learning Prediction of Extracapsular Extension in Human Papillomavirus-Associated Oropharyngeal Squamous Cell Carcinoma.

Journal: Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Published Date: Nov 1, 2020

Abstract

OBJECTIVE: To determine whether machine learning (ML) can predict the presence of extracapsular extension (ECE) prior to treatment, using common oncologic variables, in patients with human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC).

Authors

  • Kyle M Hatten
    Department of Otorhinolaryngology-Head and Neck Surgery, School of Medicine, University of Maryland, Baltimore, Maryland, USA.
  • Julian Amin
    Department of Otorhinolaryngology-Head and Neck Surgery, School of Medicine, University of Maryland, Baltimore, Maryland, USA.
  • Amal Isaiah
    Department of Otorhinolaryngology-Head and Neck Surgery, University of Maryland School of Medicine, Baltimore, MD, USA; University of Maryland Institute for Health Computing, Bethesda, MD, USA; Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA; Department of Pediatrics, University of Maryland School of Medicine, Baltimore, MD, USA. Electronic address: AIsaiah@som.umaryland.edu.

Keywords

External Resources

Popular Topics
Recent Journals