AI in Medical Imaging: A Complete Guide
Introduction
Artificial intelligence (AI) is gradually becoming an integral part of medical imaging and providing numerous positive improvements in diagnostics, workflow, and patient outcomes. With the growing implementation of AI across medical imaging, it is vital to enhance education about AI among radiography specialists in undergraduate curricula. The following article provides recommendations for integrating AI education into medical imaging based on the analysis of current literature evidence, practitioner experience, and industry perspectives.
AI is not viewed as a developing idea in medical imaging anymore because the integration of AI technologies in medical imaging is actively implemented in multiple steps of the imaging workflow. In addition, future developments of AI technologies will allow radiographers to use AI tools to analyse data at the moment of acquiring them, which means that radiographers will collaborate with AI algorithms. Therefore, the ability to analyse, evaluate, and validate AI-based results is critically important for the safe and efficient implementation of AI technologies in medical imaging.
Regulatory bodies and professional associations worldwide pay much attention to the competence of medical imaging specialists in terms of the usage of AI technologies. MRPBA, the Society of Radiographers (UK), ASRT, and RSNA emphasize the necessity to integrate AI technologies into the curriculums of undergraduate and professional education of radiographers to prepare future professionals to apply AI tools efficiently.
Healthcare systems around the world encourage the growth of the digital literacy of healthcare professionals to help them use, develop, and implement AI technologies. Universities, healthcare organisations, and government agencies introduce numerous strategies aimed at the improvement of digital literacy and modernization of healthcare education. It is clear that future healthcare professionals should not only possess the necessary skills but also know how to use them in a responsible manner.
Despite the active implementation of AI technologies in medical imaging, the development of the relevant curriculum of medical imaging education remains at its early stage due to the lack of educational materials and research. Thus, the current article provides recommendations for the inclusion of AI into the curriculum of undergraduate medical imaging education based on the current literature, practice, industry perspective, and regulatory suggestions.
Industry perspectives
Several studies evaluated the current level of the AI knowledge and competency of healthcare professionals, and it was revealed that the general level of the knowledge about AI is low despite the wide use of AI in clinical practice. Although many professionals started using AI technologies in their work, the lack of confidence and knowledge continues to exist.
Consequently, healthcare professionals should possess additional skills to manage, evaluate, and monitor the safe operation of AI technologies. Radiographers serve as the link between the latest technologies and patients' needs and should evaluate the application of AI and identify its advantages and risks.
Prominent Market Players
Conclusion
The inclusion of the curriculum of AI education in the undergraduate program of medical imaging education is crucial to prepare future radiographers for the new technology-oriented healthcare environment. The development of a structured strategy for the implementation of AI-related modules in the curriculum may allow students to get a strong foundation of AI-related knowledge and practical skills and develop critical thinking skills for the evaluation of AI application in clinical practice.
