All Outputs (2)

Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images (2022)
Journal Article
Quintero, P., Benoit, D., Cheng, Y., Moore, C., & Beavis, A. (2022). Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images. Physics in Medicine and Biology, 67(24), Article 245001. https://doi.org/10.1088/1361-6560/aca38a

Machine learning (ML) methods have been implemented in radiotherapy to aid virtual specific-plan verification protocols, predicting gamma passing rates (GPR) based on calculated modulation complexity metrics because of their direct relation to dose d... Read More about Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images.

Exploring hypoxic biology to improve radiotherapy outcomes (2022)
Journal Article
Li, C., Wiseman, L., Okoh, E., Lind, M., Roy, R., Beavis, A., & Monteiro dos Santos Pires, I. (2022). Exploring hypoxic biology to improve radiotherapy outcomes. Expert Reviews in Molecular Medicine, 24, Article E21. https://doi.org/10.1017/erm.2022.14

Ionising radiotherapy is a well-established, effective cancer treatment modality, whose efficacy has improved with the application of newer technological modalities. However, patient outcomes are governed and potentially limited by aspects of tumour... Read More about Exploring hypoxic biology to improve radiotherapy outcomes.