Unaccounted confounders limit the ability to draw conclusions from big data analysis comparing radiotherapy fractionation regimens in NSCLC

Salem, A., Franks, K., Greystoke, A. et al. (6 more authors) (2022) Unaccounted confounders limit the ability to draw conclusions from big data analysis comparing radiotherapy fractionation regimens in NSCLC. Journal of Thoracic Oncology, 17 (6). e55-e56. ISSN 1556-0864

Metadata

Item Type: Article
Authors/Creators:
Copyright, Publisher and Additional Information:

© 2022 International Association for the Study of Lung Cancer.
Keywords: Carcinoma, Non-Small-Cell Lung; Data Analysis; Humans; Lung Neoplasms
Dates:
  • Accepted: 10 January 2022
  • Published (online): June 2022
  • Published: June 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health
Depositing User: Symplectic Sheffield
Date Deposited: 14 Jul 2025 13:35
Last Modified: 14 Jul 2025 13:41
Status: Published
Publisher: Elsevier BV
Refereed: Yes
Identification Number: 10.1016/j.jtho.2022.02.010
Related URLs:
Open Archives Initiative ID (OAI ID):

Export

Statistics


CORE (COnnecting REpositories)