A multidisciplinary team and multiagency approach for AI implementation: A commentary for medical imaging and radiotherapy key stakeholders

Artificial Intelligence (AI) algorithms have been recently deployed in different healthcare settings. These tools have shown promise in reducing professionals’ administrative workload, handle electronic health records, aid drug discovery, improve diagnostic services, and analyse complex data [1-3]. Medical Imaging and Radiotherapy (MIRT) are at the forefront of this digital transformation, as can be seen from the concurrent increase in MIRT-related AI products [4-6]. In MIRT in particular, AI has shown potential to optimise image acquisition and post-processing, redefine clinical workflows, improve diagnostic accuracy, facilitate automated organ segmentation, image registration and planning in radiotherapy, and personalise patient care [7-9]. These recent advancements could translate into improved patient outcomes, personalised pathways and treatment plans, and, therefore, deliver precision into healthcare [10,11]. At the same time, concerns about potential risks and safety of AI-enabled software and hardware are raised by both clinical practitioners and patients, which need to be addressed within the design and implementation of AI and balanced against the undoubted benefits [12].