Radioprotection 2025, 60( 4), 310 – 317 © B. Amaoui et al., Published by EDP Sciences 2025 https:// doi. org / 10.1051 / radiopro / 2025013 Available online at: www. radioprotection. org
ARTICLE
Knowledge and perception of Moroccan onco-radiotherapists on the contribution of artificial intelligence to their practices
B. Amaoui 1,*, M. El Fahssi 2, H. El Kacemi 3, M. Zerfaoui 4 and S. Semghouli 5
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. Received: 19 December 2024 / Accepted: 14 April 2025
Abstract – 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.
Keywords: artificial intelligence / onco-radiotherapist / image acquisition / image reconstruction / radiotherapy / Morocco
1 Introduction
The artificial intelligence( AI) is increasingly being integrated into various aspects of healthcare, bringing notable improvements across domains such as the diagnosis and treatment of diseases. These technological advances have enabled better quality of care and facilitated the analysis of large volumes of patient data, which has had a enhanced diagnostic accuracy of medical diagnoses and the more effective treatment plans( Pulimamidi, 2023; Mittal and Mantri 2023;). In fact, AI has the potential to transform many aspects of healthcare( Kulkarni et al., 2020;). In this context, AI technologies can improve the ability to identify patient
* e-mail: b. amaoui @ uiz. ac. ma responses to treatments, normalise patient data to eliminate redundancies in stored data, reduce patient waiting times, target therapies to improve therapeutic outcomes, enhance advanced analytics to include predictive, descriptive, diagnostic, and prescriptive analysis, and minimise waste( Anom, 2020). Furthermore, AI has also yielded substantial benefits to the field of medical radiology, particularly in automating the quantitative assessment of complex features in medical images, which has considerably improving diagnostic precision and operational efficiency. The introduction of AI into medical imaging has led to more accurate diagnoses and a significant reduction in doctors’ workloads( Zhou et al., 2019).
In radiotherapy, AI has rapidly facilitating the complex and lengthy process of preparing a patient for treatment sessions. AI solutions can harmonize structure definitions and nomenclature, allocate tasks across clinical teams, help improve
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