City Research Online

Abstract

OBJECTIVES: This paper will outline the status and basic principles of artificial intelligence (AI) in radiography along with some thoughts and suggestions on what the future might hold. While the authors are not always able to separate the current status from future developments in this field, given the speed of innovation in AI, every effort has been made to give a view to the present with projections to the future.

KEY FINDINGS: AI is increasingly being integrated within radiography and radiographers will increasingly be working with AI based tools in the future. As new AI tools are developed it is essential that robust validation is undertaken in unseen data, supported by more prospective interdisciplinary research. A framework of stronger, more comprehensive approvals are recommended and the involvement of service users, including practitioners, patients and their carers in the design and implementation of AI tools is essential. Clearer accountability and medicolegal frameworks are required in cases of erroneous results from the use of AI-powered software and hardware. Clearer career pathways and role extension provision for healthcare practitioners, including radiographers, are required along with education in this field where AI will be central.

CONCLUSION: With the current growth rate of AI tools it is expected that many of the applications in medical imaging will continue to develop to more accurate, less expensive and more readily available versions moving from the bench to the bedside. The hope is that, alongside efficiency and increased patient throughput, patient centred care and precision medicine will find their way in, so we will not only deliver a faster, safer, seamless clinical service but also one that will have the patients at its heart.

IMPACT FOR PRACTICE: AI is already reaching clinical practice in many forms and its presence will continue to increase over the short and long-term future. Radiographers must learn to work with AI, embracing it and maximising the positive outcomes from this new technology.

Publication Type:	Article
Additional Information:	© 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords:	Artificial intelligence, Diagnostic radiography, Therapeutic radiography, Future vision, Implementation
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RC Internal medicine
Departments:	School of Health & Psychological Sciences > Midwifery & Radiography
SWORD Depositor:	Symplectic Administrator

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