Our Work
Radiology and radiation oncology have always been at the forefront of technology adoption in the healthcare industry. These are two areas of medicine are data rich and already using advanced technologies and informatics software. AI is already proving to be impactful on these disciplines, and the technology is evolving fast.
AI has the capacity to aid clinicians in diagnostics and patient management, as well as a prognostic and predictive tool. However, in order to realise the full benefits of AI, safeguards need to be in place. This includes but is not limited to:
RANZCR is committed to guiding the safe deployment of AI into clinical practice, to ensure the best possible outcomes for patients and health care workers.
RANZCR commenced work on AI in 2017, and in 2018 formed an AI Working Group which was later converted to an advisory committee. In 2019 we published a landscape paper (Artificial Intelligence: The State of Play 2019 | RANZCR) outlining the impact AI could have on our professions, which outlines the risks and opportunities that AI could bring to our sectors. The AI Committee has since continued to develop content to help guide the safe use of AI in clinical practice and advocate to decision makers and regulators to implement appropriate oversight of the technology at the highest level. RANZCR has also compiled definitions of general AI terms which can be broadly applied to its AI work.
The College actively engages with governments, industry, consumers and other stakeholders in clinical radiology and radiation oncology to ensure consumers have access to quality services. RANZCR consults broadly on all AI work, as this is a rapidly evolving field, and collaboration helps us ensure that a wide spectrum of views are considered.
From an AI perspective, the following have been developed to guide stakeholders in the use of AI:
RANZCR has developed nine ethical principles which inform the development of professional and practice standards regarding the research and deployment of AI in medicine. These principles are intended to guide all stakeholders involved in research or deployment of ML and AI including developers, health service executives and clinicians.
AI technology in healthcare is rapidly evolving and checks and balances are needed to ensure patient safety. While autonomous AI promises improvements to efficiency and speed, risks to patient outcomes must be carefully considered prior to implementation. RANZCR advocates for a human in the loop approach to ensure this technology is safely utilised. Published August 2024
Autonomous AI Position Paper
RANZCR recognises the potential for AI to enhance and expedite patient care, and also acknowledges the importance of users understanding the risks and specific requirements of AI tools prior to use in a clinical setting. Published August 2024
Generative Artificial Intelligence and Large Language Models
RANZCR advocates for effective regulation that provides clarity for AI developers and the rest of the healthcare system while safeguarding patient care. The position paper sets out principles and recommendations to guide the development of a robust regulatory framework for AI technology in medicine.
A multi-society paper presenting the views of Radiology Societies in the USA, Canada, Europe, Australia, and New Zealand, this editorial defines the potential practical problems and ethical issues surrounding the incorporation of AI into radiological practice. It also delineates the main points of concern that developers, regulators, and purchasers of AI tools should consider prior to their introduction into clinical practice, and suggests methods to monitor their stability and safety in clinical use, and their suitability for possible autonomous function.
RANZCR and the AI Committee have written the following submissions to external AI related consultations:
RANZCR is committed to setting, promoting and continuously improving standards of practice for clinical radiology and radiation oncology for the betterment of the people of Australia and New Zealand. The Standards are designed to assist members in achieving best practice. The AI specific Standards for clinical radiology can be found in chapter nine, and the radiation oncology standards are linked below as a standalone module currently undergoing consultation.
Clinical Radiology Standards of Practice
Radiation Oncology AI Practice Standards
Artificial Intelligence (AI) can help clinicians to better diagnose illness, coordinate treatment plans and increase the efficiency of care delivery across healthcare. It allows for a more efficient and accessible healthcare system that delivers improved outcomes for patients.
To provide members with the opportunity to increase their awareness and understanding of AI, faculty specific online resources are available below.
The current state and future trajectory