Comparison of time-to-event machine learning models in predicting oral cavity cancer prognosis.

Journal: International journal of medical informatics
Published Date: Nov 14, 2021

Abstract

BACKGROUND: Applying machine learning to predicting oral cavity cancer prognosis is important in selecting candidates for aggressive treatment following diagnosis. However, models proposed so far have only considered cancer survival as discrete rather than dynamic outcomes.

Authors

  • John Adeoye
    Oral and Maxillofacial Surgery, Faculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region.
  • Liuling Hui
    Oral and Maxillofacial Surgery, Faculty of Dentistry, The University of Hong Kong, Hong Kong, China.
  • Mohamad Koohi-Moghadam
    Department of Health Sciences Research and Center for Individualized Medicine, Mayo Clinic, Scottsdale, Arizona, USA.
  • Jia Yan Tan
    Oral and Maxillofacial Surgery, Faculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region. Electronic address: jiayant@hku.hk.
  • Siu-Wai Choi
    Oral and Maxillofacial Surgery, Faculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region. Electronic address: htswchoi@hku.hk.
  • Peter Thomson
    Oral and Maxillofacial Surgery, Faculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region.

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