Astley, J.R., Reilly, J., Robinson, S. et al. (3 more authors) (2024) 1596: The impact of dosimetric features on interpretable overall survival prediction in NSCLC radiotherapy. In: Radiotherapy and Oncology. ESTRO 2024, 03-07 May 2024, Glasgow, UK. Elsevier BV , S4488-S4492.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Authors. Except as otherwise noted, this author-accepted version of an abstract published in Radiotherapy and Oncology is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Physical Sciences; Biomedical and Clinical Sciences; Oncology and Carcinogenesis; Lung Cancer; Cancer; Lung; Radiation Oncology; Radiotherapy and other non-invasive therapies; Cancer; Good Health and Well Being |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health |
Funding Information: | Funder Grant number YORKSHIRE CANCER RESEARCH S422 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 11 Jul 2025 15:13 |
Last Modified: | 11 Jul 2025 15:28 |
Status: | Published |
Publisher: | Elsevier BV |
Identification Number: | 10.1016/s0167-8140(24)01965-0 |
Related URLs: | |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:229102 |
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Filename: ESTRO2024 abstract_v3 machine learning (2).pdf
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