Machine Learning Methods in Classification of Prolonged Radiation Therapy in Oropharyngeal Cancer: National Cancer Database.

Journal: Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
PMID: 39082895

Abstract

OBJECTIVE: To investigate the accuracy of machine learning (ML) algorithms in stratifying risk of prolonged radiation treatment duration (RTD), defined as greater than 50 days, for patients with oropharyngeal squamous cell carcinoma (OPSCC).

Authors

  • Seungjun Ahn
    Institute for Healthcare Delivery Science, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York City, New York, USA.
  • Eun Jeong Oh
    Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
  • Matthew I Saleem
    Department of Otolaryngology-Head and Neck Surgery, Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA.
  • Tristan Tham
    Department of Otolaryngology-Head and Neck Surgery, Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA.

Keywords

External Resources

Popular Topics
Recent Journals