Artificial Intelligence-suggested Predictive Model of Survival in Patients Treated With Stereotactic Radiotherapy for Early Lung Cancer.

Journal: In vivo (Athens, Greece)
PMID: 38688600

Abstract

BACKGROUND/AIM: Overall survival (OS)-predictive models to clinically stratify patients with stage I Non-Small Cell Lung Cancer (NSCLC) undergoing stereotactic body radiation therapy (SBRT) are still unavailable. The aim of this work was to build a predictive model of OS in this setting.

Authors

  • Paolo Borghetti
    Radiation Oncology Department, Spedali Civili and University of Brescia, Brescia, Italy.
  • Gianluca Costantino
    Radiation Oncology Department, Humanitas-Gavazzeni, Bergamo, Italy.
  • Valeria Santoro
    Azienda Ospedaliera Universitaria Integrata Verona, Radiation Oncology, Verona, Italy.
  • Eneida Mataj
    Radiation Oncology Department, Spedali Civili and University of Brescia, Brescia, Italy; e.mataj@unibs.it.
  • Navdeep Singh
    Radiation Oncology Department, Spedali Civili and University of Brescia, Brescia, Italy.
  • Paola Vitali
    Radiation Oncology Department, Spedali Civili and University of Brescia, Brescia, Italy.
  • Diana Greco
    Radiation Oncology Department, Spedali Civili and University of Brescia, Brescia, Italy.
  • Giulia Volpi
    Azienda Ospedaliera Universitaria Integrata Verona, Radiation Oncology, Verona, Italy.
  • Matteo Sepulcri
    Radiotherapy Unit, Veneto Institute of Oncology IOV - IRCCS, Padua, Italy.
  • Cesare Guida
    Radiotherapy Unit, Ospedale del Mare, ASL Napoli 1, Naples, Italy.
  • Cesare Tomasi
    D.S.M.C, University of Brescia, Brescia, Italy.
  • Michela Buglione
    Radiation Oncology Department, Spedali Civili and University of Brescia, Brescia, Italy.
  • Valerio Nardone
    Department of Precision Medicine, University of Campania "L. Vanvitelli", Naples, Italy.

Keywords

External Resources

Popular Topics
Recent Journals