A dosiomics model for prediction of radiation-induced acute skin toxicity in breast cancer patients: machine learning-based study for a closed bore linac.

Journal: European journal of medical research
PMID: 38735974

Abstract

BACKGROUND: Radiation induced acute skin toxicity (AST) is considered as a common side effect of breast radiation therapy. The goal of this study was to design dosiomics-based machine learning (ML) models for prediction of AST, to enable creating optimized treatment plans for high-risk individuals.

Authors

  • Pegah Saadatmand
    Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
  • Seied Rabi Mahdavi
    Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran. srmahdavi@hotmail.com.
  • Alireza Nikoofar
    Department of Radiation Oncology, Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran. Electronic address: arnikoofar@gmail.com.
  • Seyede Zohreh Jazaeri
    Department of Neuroscience, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran.
  • Fahime Lamei Ramandi
    Radiotherapy Department, Pars Hospital, Tehran, Iran.
  • Golbarg Esmaili
    Radiotherapy Department, Pars Hospital, Tehran, Iran.
  • Soheil Vejdani
    Department of Radiation Oncology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.

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