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Abstract

Artificial Intelligence (AI) algorithms are now being adopted and evaluated across a range of healthcare settings. Novel AI-based applications can reduce administrative workload of professionals, manage electronic health records, aid drug discovery, improve diagnostic services, and analyse complex and large amounts of data (Han et al., 2024; Al Kuwaiti et al., 2023; Wichmann et al., 2020). Medical Imaging and Radiotherapy (MIRT) are at the forefront of this digital transformation (Akudjedu et al., 2023). This trend is matched by the concurrent increase in MIRT-related AI products (van Leeuwen et al., 2024; Health Imaging, 2024; FDA, 2024). AI is acting as a catalyst for MIRT, and could, revolutionise image acquisition and analysis, redefine clinical workflows, improve diagnostic accuracy, provide automated organ segmentation, image registration and planning in radiotherapy, and customise patient care (Fu et al., 2022; Najjar, 2023; Landry et al., 2023). These recent AI advancements could translate into improved patient outcomes, personalised pathways and treatment plans, and, therefore, delivery of optimal health services adapted to each person (Pinto-Coelho, 2023; Brady et al., 2024).

Being at the front of this technological advancement comes with substantial costs; As AI applications emerge, are tested and are rigorously evaluated, MIRT professionals will have the responsibility of ensuring that the implementation of AI in clinical practice is optimised, monitored, and guided by robust governance principles, therefore following best practice. While each profession works to understand what AI implementation might has on clinical workflows, their future roles and careers, it is of paramount importance that each discipline also considers the challenges of AI implementation such as knowledge gaps, training, and the wider workforce (Walsh et al., 2023).

Publication Type:	Article
Additional Information:	© 2024. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RC Internal medicine T Technology > T Technology (General)
Departments:	School of Health & Psychological Sciences School of Health & Psychological Sciences > Healthcare Services Research & Management School of Health & Psychological Sciences > Midwifery & Radiography School of Science & Technology School of Science & Technology > Computer Science
SWORD Depositor:	Symplectic Administrator

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