Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer.

Journal: International journal of medical informatics
Published Date:

Abstract

BACKGROUND: The proper estimate of the risk of recurrences in early-stage oral tongue squamous cell carcinoma (OTSCC) is mandatory for individual treatment-decision making. However, this remains a challenge even for experienced multidisciplinary centers.

Authors

  • Rasheed Omobolaji Alabi
    Department of Industrial Digitalization, School of Technology and Innovations, University of Vaasa, Vaasa, Finland.
  • Mohammed Elmusrati
    Department of Industrial Digitalization, School of Technology and Innovations, University of Vaasa, Vaasa, Finland.
  • Iris Sawazaki-Calone
    Oral Pathology and Oral Medicine, Dentistry School, Western Parana State University, Cascavel, PR, Brazil.
  • Luiz Paulo Kowalski
    Department of Head and Neck Surgery and Otorhinolaryngology, AC Camargo Cancer Center, Sao Paulo, Brazil.
  • Caj Haglund
    Research Programs Unit, Translational Cancer Biology, University of Helsinki, Helsinki, Finland.
  • Ricardo D Coletta
    Department of Oral Diagnosis, School of Dentistry, University of Campinas, Piracicaba, São Paulo, Brazil.
  • Antti A Mäkitie
    Department of Otorhinolaryngology - Head and Neck Surgery, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
  • Tuula Salo
    Department of Pathology, University of Helsinki, Helsinki, Finland.
  • Alhadi Almangush
    Research Programme in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland. alhadi.almangush@helsinki.fi.
  • Ilmo Leivo
    Institute of Biomedicine, Pathology, University of Turku, Turku, Finland.