Predicting overall survival in anaplastic thyroid cancer using machine learning approaches.

Journal: European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PMID: 39305341

Abstract

PURPOSE: Anaplastic thyroid carcinoma (ATC) is a highly aggressive and lethal thyroid cancer subtype with a poor prognosis. Recent advancements in machine learning (ML) have the potential to improve survival predictions. This study aimed to develop and validate ML models using the SEER database to predict 3-month, 6-month, and 12-month (overall survival) OS in ATC patients.

Authors

  • Arnavaz Hajizadeh Barfejani
    Royal College of Surgeons in Ireland, Dublin, Ireland.
  • Mohammadreza Rostami
    Xi'an Jiaotong University, Xi'an, China.
  • Mohammad Rahimi
    Student Research Committee, School of Medicine, Mazandaran University of Medical Sciences, Mazandaran, Iran.
  • Hossein Sabori Far
    Chaloos Razi Hospital, Mazandaran, Iran.
  • Shahab Gholizadeh
    Chaloos Razi Hospital, Mazandaran, Iran.
  • Morteza Behjat
    Department of Orthopedic Surgery, Rasoul-e-Akram Hospital, Iran University of Medical Sciences, Tehran, Iran.
  • Aidin Tarokhian
    Medical School, Hamadan University of Medical Sciences, Pajoohesh Blvd, Hamadan, Iran. tarokhianaidin@gmail.com.

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