Artificial intelligence: the impact on clinical radiology and clinical oncology

RCR leading the way 

There is much investment in research and development of artificial intelligence (AI) across healthcare, with the hope of reaping great rewards. The RCR as standard setter for its two specialties of clinical radiology and clinical oncology will lead in establishing the framework for AI. The RCR has defined four broad work streams:

  1. Defining AI and associated terminology
  2. Establishing the framework for regulation
  3. Quality assurance as AI implementation comes on stream
  4. Engagement and partnership working

Defining artificial intelligence

The College will engage with stakeholders to define terms used in and around this sector which include:

  • Machine learning
  • Deep learning
  • Artificial intelligence.


There is as yet no regulatory framework for AI in healthcare.The RCR will collaborate with stakeholders and focus on a number of principles:

  • Accountability – where does/should accountability lie for the development, testing, and clinical introduction of AI.
  • Veracity – arriving at an accepted standard for data validation.
  • Reactivity – as AI evolves, what are the trigger points to future-proof the framework.
  • Interoperability – the framework should be relevant and applicable across all AI developments. AI software products should integrate seamlessly and fully, using vendor-neutral international interoperability standards, into extant digital healthcare systems such as PACS, RIS and the EPR.

Quality assurance

Quality assurance must pervade all stages of the development of AI through to implementation and beyond. The RCR will develop standards for validation of data and algorithms to safeguard patient outcomes.

Engagement and partnership working

There are three strands to engagement and partnership working:

  • Harnessing AI expertise
  • Training and development
  • Collating existing datasets for the public benefit.

Through these strands, the RCR will become a source of expertise for the media.

On harnessing expertise, the RCR will provide a platform for all: the NHS and its stakeholder organisations, academic communities, industry and, most importantly, patients. The RCR is free from commercial interest or bias and not within the competitive academic world and so will be an honest broker.

On training, the clinical radiology and clinical oncology postgraduate training curricula are being rewritten including interpreting data in the broadest sense.

On datasets, there is a need for vast amounts of anonymised, appropriately validated electronic patient data in order to train AI technology. The RCR will bring together the key players to enable equitable access to existing and new datasets so as to protect patient data and ensure the NHS retains the benefits of its intellectual property.