Decision tree-based machine learning algorithm for prediction of acute radiation esophagitis.

Journal: Biochemistry and biophysics reports
Published Date: Mar 28, 2025

Abstract

BACKGROUND: Radiation-induced esophagitis remains a significant challenge in thoracic and neck cancer treatment, impacting patient quality of life and potentially limiting therapeutic efficacy. This study aimed to develop and validate a decision tree-based model for predicting acute esophagitis grades in patients undergoing chemoradiotherapy.

Authors

  • Mostafa Alizade-Harakiyan
    Department of Radiation Oncology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Amin Khodaei
    Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
  • Ali Yousefi
  • Hamed Zamani
    Medical Physics Department, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Asghar Mesbahi
    Medical Physics Department, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.

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