The PICTURES programme of work is about increasing the capabilities of Safe Havens to support emerging technologies such as artificial intelligence (AI) and new data types such as images, MRIs, CTs, Xrays etc in health data research.
Safe Havens were introduced in Scotland around 2008 as places where pseudonymised linked health data could be made available for approved research in a safe and secure manner.
As diagnostic technologies improved, vast amounts of high-quality clinical image data have become available. Every x-ray, CT scan, ultrasound and MRI contains a wealth of information – not just about disease but also about what healthy bodies look like. As compute power has increased, the tools and knowledge for tapping into data have become more common.
Data science now provides the means to support medical practitioners through machine learning and AI. AI in health care can help speed up diagnoses by computing vast amounts of information in seconds, easing the reporting burden for Radiologists by pre-populating routine fields of information for them and spotting disease early through pattern recognition. For diseases such as cancer, early detection from imaging greatly improves the chances of survival.
Machine learning works best when it is trained on very large datasets containing all the patterns we want it to recognise. Those patterns can be found in the images and other health data collected through routine visits to healthcare settings. AI can detect subtle changes invisible to the human eye and will give consistent results 24×7 which even the best radiologists cannot deliver 100% of the time.
The PICTURES programme aims to identify best practice for both the technical environment and governance of safe havens to allow such research to happen safely and securely. Associated challenges are manipulating large volumes of data (a petabyte of data could be held on 1.5million CD-ROMs), deploying machine learning tools, importing and exporting of software code whilst preserving privacy and minimising the risk of data leakage. But most importantly, we need to maintain the trust of the public that enabling all this is for the greater good.
Find out more project details, see progress on our timeline and read stories from the team on our blog page.
