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Selecting patients for proton beam therapy

Name: Selecting patients for proton beam therapy
Creator: Verity Ahern
Keywords: Patient Selection, R895-920, Markov model, Markov Chains, 3. Good health, proton beam therapy, Medical physics. Medical radiology. Nuclear medicine, 03 medical and health sciences, Editorial, 0302 clinical medicine

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 01 Dec 2020Publisher:WileyJournal:Journal of Medical Radiation Sciences, volume 68, pages 2-3 (issn: 2051-3895, eissn: 2051-3909,

Authors: Verity Ahern;

doi: 10.1002/jmrs.454

pmid: 33259660

pmc: PMC7890916

Selecting patients for proton beam therapy

- Summary
- Subjects
- Metrics

Abstract

A transparent and equitable process for selecting patients who will benefit most from treatment at the Australian Bragg Centre for Proton Therapy as well as providing cost benefit for the investment made by government for this valuable resource, needs to be in place as soon as the Centre becomes operational, particularly for patients with more common cancers. Markov modelling is one method of patient selection and an example is provided in this issue of the Journal of Medical Radiation Sciences.

Related Organizations

University of Sydney
Australia

Keywords

Patient Selection, R895-920, Markov model, Markov Chains, proton beam therapy, Medical physics. Medical radiology. Nuclear medicine, Editorial, Neoplasms, Proton Therapy, patient selectin, Humans

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	8
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%