Exploring patient stratification in head and neck squamous cell carcinoma using machine learning techniques: Preliminary results.

Journal: Current problems in cancer
PMID: 39488997

Abstract

BACKGROUND: Head and Neck Squamous Cell Carcinoma (HNSCC) presents a significant challenge in oncology due to its inherent heterogeneity. Traditional staging systems, such as TNM (Tumor, Node, Metastasis), provide limited information regarding patient outcomes and treatment responses. There is a need for a more robust system to improve patient stratification.

Authors

  • Giovanni Lilloni
    Maxillofacial Unit, University-Hospital of Parma, Italy. Electronic address: giovanni.lilloni.md@gmail.com.
  • Giuseppe Perlangeli
    Maxillofacial Unit, University-Hospital of Parma, Italy.
  • Francesca Noci
    Interdisciplinary Research Center for Health Science, Sant'Anna School of Advanced Studies, Pisa, 56127, Italy.
  • Silvano Ferrari
    Maxillofacial Unit, University-Hospital of Parma, Italy.
  • Alessandro Dal Palù
    Department of Mathematical Physical and Computer Sciences, University of Parma, Italy.
  • Tito Poli
    Maxillofacial Unit, University-Hospital of Parma, Italy.

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