Toxicity Prediction in Pelvic Radiotherapy Using Multiple Instance Learning and Cascaded Attention Layers

Elhaminia, B, Gilbert, A orcid.org/0000-0002-9142-1227, Lilley, J et al. (5 more authors) (2023) Toxicity Prediction in Pelvic Radiotherapy Using Multiple Instance Learning and Cascaded Attention Layers. IEEE Journal of Biomedical and Health Informatics, 27 (4). pp. 1958-1966. ISSN 2168-2194

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Item Type: Article
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Keywords: deep learning , multiple instance learning , radiotherapy , outcome prediction , toxicity map
Dates:
  • Published: 5 April 2023
  • Published (online): 23 January 2023
  • Accepted: 14 January 2023
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds)
The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Inst of Biomed & Clin Sciences (LIBACS) (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 10 Mar 2023 16:20
Last Modified: 22 May 2024 01:22
Status: Published
Publisher: IEEE
Identification Number: 10.1109/jbhi.2023.3238825
Open Archives Initiative ID (OAI ID):

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