The RCR believes that artificial intelligence (AI), machine learning (ML) and associated health technologies represent one of the most potentially fundamental changes in medical care since the inception of the NHS. We strongly welcome the introduction of appropriately regulated and governed uses of AI related technologies to augment clinical practice. Far from making the clinical radiologist and clinical oncologist of the future redundant, as some press has suggested, the use of AI will help standardise many aspects of clinical care, will optimise processes and allow greater use of clinical data to inform best practice and outcomes.
For these technologies to translate into patient benefit and clinician support as swiftly and smoothly as possible, we are urging all developers to synergise on the following core principles:
- Work to common standards that facilitate universal applicability, including extant standards for clinical practice as set out by the RCR as well as other stakeholders including the National Institute for Health and Care Excellence (NICE)
- Assure the quality, safety and security of data used
- Take account of current and emerging regulation by healthcare and digital economy regulators
- Be clinically led so that effort is directed where it can most readily be used in practice to relieve hard-pressed NHS services
- Achieve the widest possible use of digital data for the benefit of UK patients and the population as a whole.
Our priority is to support all our Fellows and members in becoming early adopters of AI, and embracing these technologies as they develop. We want to equip Fellows and members to be confident in integrating AI technologies into routine medical practice.
We plan to increase our work in this area over the coming months and years given its importance.
Imaging Datasets that can used for Research Purposes
Imaging datasets are incredibly important for AI research. The following web page contains a list of imaging datasets that can be used for research purposes. It gives some basic information about what data is available and what the permissions are; for example, academic access or also for commercial use and so on.
A collection of open source imaging data sets
* With thanks to the NIHR and Professor Rockall for this information