An ICTP-IAEA Meeting in person
The workshop is designed for medical physicists having interest in expanding their knowledge and skills to implement AI-based tools. It will provide a contemporary overview of the field and introduce to medical physicists theoretical principles which are considered fundamental for a safe and conscious implementation of AI-based technologies in radiation medicine.
This comprehensive workshop will provide participants with a theoretical foundation in the most important research and technological development areas of AI-based tools in radiation medicine. The workshop with introduce to medical physicists examples of AI-based tools in radiation medicine practice and relevant theoretical foundations, and will discuss technical, ethical, and legal challenges associated with clinical implementation of AI-based tools that should be carefully considered to ensure that quality of patient care and patient safety are not compromised. Given the roles and responsibilities of medical physicists in the technical supervision of radiation medicine equipment, it is imperative to contextualize and extend these responsibilities to the implementation, risk mitigation, and quality assurance of AI-based tools in radiation medicine. This workshop will introduce to medical physicists the theoretical knowledge and skills necessary to implement AI-based tools safely and securely, emphasizing the need for continued education and training in this emerging field.
The Workshop is aimed at providing medical physicist with relevant knowledge to support departments in deploying and using AI based tools, including:
The target audience are early and mid-career clinically qualified medical physicists (CQMPs, as per IAEA Publication Human Health Series No. 25) from United Nations, UNESCO or IAEA Member States holding a postgraduate-level university degree in medical physics and working in hospitals in either in radiotherapy, nuclear medicine or diagnostic radiology. Although the workshop is not intended for developers of AI-based tools, basic computational programming, data management and fundamental statistics skills are considered as assets.