Machine learning prediction model for oral mucositis risk in head and neck radiotherapy: a preliminary study.

Journal: Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PMID: 39808310

Abstract

PURPOSE: Oral mucositis (OM) reflects a complex interplay of several risk factors. Machine learning (ML) is a promising frontier in science, capable of processing dense information. This study aims to assess the performance of ML in predicting OM risk in patients undergoing head and neck radiotherapy.

Authors

  • Elisa Kauark-Fontes
    Department of Propaedeutic and Integrated Clinic, Universidade Federal da Bahia (UFBA), Salvador, Bahia, Brazil. elisakauark@gmail.com.
  • Anna Luíza Damaceno Araújo
    Oral Diagnosis Department, Piracicaba Dental School, University of Campinas (FOP-UNICAMP), Piracicaba, São Paulo, Brazil.
  • Danilo Oliveira Andrade
    Department of Computer Science, Federal University of Bahia, Salvador, Brazil.
  • Karina Morais Faria
    Dental Oncology Service, Instituto Do Câncer Do Estado de São Paulo (ICESP), Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil.
  • Ana Carolina Prado-Ribeiro
    Oral Diagnosis Department (Pathology and Semiology), Piracicaba Dental School, University of Campinas, Piracicaba, Brazil; Dental Oncology Service, Instituto do Câncer do Estado de São Paulo (ICESP-FMUSP), São Paulo, Brazil.
  • Alexa Laheij
    Department of Oral Medicine, Academic Center for Dentistry Amsterdam, University of Amsterdam and VU University Amsterdam, Amsterdam, Netherlands.
  • Ricardo Araújo Rios
    Department of Computer Science, Federal University of Bahia, Salvador, Brazil.
  • Luciana Maria Pedreira Ramalho
    Department of Propaedeutic and Integrated Clinic, Universidade Federal da Bahia (UFBA), Salvador, Bahia, Brazil.
  • Thaís Bianca Brandão
    Dental Oncology Service, Instituto do Câncer do Estado de São Paulo (ICESP-FMUSP), São Paulo, Brazil.
  • Alan Roger Santos-Silva
    Oral Diagnosis Department (Pathology and Semiology), Piracicaba Dental School, University of Campinas, Piracicaba, Brazil.

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