RAIR's repository stores historical structured and unstructured real-world data from a population of over 4m people, held in a single, secure, state-of-the-art electronic data storage structure.
The NHS collects crale-tograve records on everyone in the country. Research into chronic disease, in particular, place significant value on these types of data. But it can take years to negotiate access to these records, which are spread across multiple organisations and departments, and still longer to piece all of the data together. The quality of health data is also notoriously variable: Missing, incorrect and heterogeneous data necessitate laborious manual processes which can consume a large proportion of and data science project's budget.
In addition to Real-World Data, RAIR uses AI to extract "New Data" from the unstructured data, such as images and doctors notes: Images, in particular, contain vast amounts of sequestered information which is un-tainted by the human errors and omissions which undermine the value of more readily available structured real-world data.
RAIR aggregate the Real-World Data, New Data - collectively we call this "New Information" - in a data lake which provides a single point of access for researchers.
No repository like this exists anywhere else in the world and it is our hope that this will enable researchers to answer questions about disease, including those chronic disorders whose origins pre-date the diagnosis by years, which might otherwise be impossible to answer.
We take the security of the data in the repository extremely seriously. If you would like to learn more about the measures that we have implemented to protect the confidentiality of the data in the repository, please click on the button below.
Gurjeet Singh, CEO Ayasdi.com
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