Machine learning explainability for survival outcome in head and neck squamous cell carcinoma.

Journal: International journal of medical informatics
PMID: 40121767

Abstract

BACKGROUND: Diagnosis and treatment of head and neck squamous cell carcinoma (HNSCC) induces psychological variables and treatment-related toxicity in patients. The evaluation of outcomes is warranted for effective treatment planning and improved disease management.

Authors

  • Rasheed Omobolaji Alabi
    Department of Industrial Digitalization, School of Technology and Innovations, University of Vaasa, Vaasa, Finland.
  • Antti A Mäkitie
    Department of Otorhinolaryngology - Head and Neck Surgery, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
  • Mohammed Elmusrati
    Department of Industrial Digitalization, School of Technology and Innovations, University of Vaasa, Vaasa, Finland.
  • Alhadi Almangush
    Research Programme in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland. alhadi.almangush@helsinki.fi.
  • Ylva Tiblom Ehrsson
    Department of Surgical Sciences, Section of Otorhinolaryngology and Head and Neck Surgery, Uppsala University, Uppsala, Sweden.
  • Göran Laurell
    Department of Surgical Sciences, Section of Otorhinolaryngology and Head and Neck Surgery, Uppsala University, Uppsala, Sweden.

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