Artificial intelligence in radiation oncology: A review of its current status and potential application for the radiotherapy workforce

Parkinson, C., Matthams, C., Foley, K. and Spezi, E. ORCID: https://orcid.org/0000-0002-1452-8813 2021. Artificial intelligence in radiation oncology: A review of its current status and potential application for the radiotherapy workforce. Radiography 27 , S63-S68. 10.1016/j.radi.2021.07.012

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Abstract

Objective Radiation oncology is a continually evolving speciality. With the development of new imaging modalities and advanced imaging processing techniques, there is an increasing amount of data available to practitioners. In this narrative review, Artificial Intelligence (AI) is used as a reference to machine learning, and its potential, along with current problems in the field of radiation oncology, are considered from a technical position. Key Findings AI has the potential to harness the availability of data for improving patient outcomes, reducing toxicity, and easing clinical burdens. However, problems including the requirement of complexity of data, undefined core outcomes and limited generalisability are apparent. Conclusion This original review highlights considerations for the radiotherapy workforce, particularly therapeutic radiographers, as there will be an increasing requirement for their familiarity with AI due to their unique position as the interface between imaging technology and patients. Implications for practice Collaboration between AI experts and the radiotherapy workforce are required to overcome current issues before clinical adoption. The development of educational resources and standardised reporting of AI studies may help facilitate this.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	Elsevier
ISSN:	1078-8174
Date of First Compliant Deposit:	8 October 2021
Date of Acceptance:	21 July 2021
Last Modified:	06 Nov 2023 20:02
URI:	https://orca.cardiff.ac.uk/id/eprint/144759

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