| Issue |
Radioprotection
Volume 60, Number 4, Octobre-Décembre 2025
|
|
|---|---|---|
| Page(s) | 310 - 317 | |
| DOI | https://doi.org/10.1051/radiopro/2025013 | |
| Published online | 15 December 2025 | |
Article
Knowledge and perception of Moroccan onco-radiotherapists on the contribution of artificial intelligence to their practices
1
Biotechnology and Medicine (BioMed) Laboratory, Faculty of Medicine and Pharmacy, Ibn Zohr University, Agadir, Morocco
2
Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, Morocco
3
National Institute of Oncology, Rabat, Morocco
4
Faculty of Science, Mohammed 1 St University, Oujda, Morocco
5
Team Health Techniques (ETechS), Research Laboratory in Health and Environmental Sciences (LabReSSE), Higher Institute of Nursing Professions and Health Techniques (ISPITS), Agadir, Morocco
* e-mail: b.amaoui@uiz.ac.ma
Received:
19
December
2024
Accepted:
14
April
2025
Introduction: The introduction of AI into medical practice increasingly evident. healthcare professionals and institutions in the sector in Morocco must support this change to optimise the expected benefits of this technology. Objective: This retrospective study aimed to assess the knowledge and perceptions of Moroccan onco-radiotherapists regarding the contribution of artificial intelligence to clinical practice. Materials and methods: A anonymised questionnaire of 19 questions distributed via email address to two participant groups: the onco-radiotherapists (G1) and the Onco-Radiotherapy Residents (G2). To compare the responses between the two participant groups, Fisher’s exact test of the statistical tool for the social sciences (SPSS version 21.0) was used. The value P < 0.05 indicates that the difference is statistically significant. Results: 60% of the G1s stated that they had moderate knowledge of AI, whereas 72% of the G2s stated that they reported limited knowledge of AI. 50% of G1s and 61.5% of G2s have not received sufficient knowledge or training to use AI technologies safely and effectively. The majority of participants believed that AI would positively impact the productivity of radiotherapy practices in image acquisition and reconstruction. In addition, most participants believed that AI techniques would enhance the quality of interventions and image reconstruction functions. Most participants were optimistic about the use of AI in radiotherapy. However, almost 40% of G1s and 46% of G2s believe AI might impact their current role. Conclusion: AI certainly brings many benefits to medical practices; nevertheless, the investment in infrastructure, workforce training, and legal frameworks are urgent measures to be taken.
Key words: artificial intelligence / onco-radiotherapist / image acquisition / image reconstruction / radiotherapy / Morocco
© B. Amaoui et al., Published by EDP Sciences 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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