– Smart Patient Record Format for standardising representation of decentralised health data
– Blockchain Technology for controlling the access to sensitive data
– Serums Data Lake and Metadata Extraction Technology that will use machine learning to structure data collected from various sources
– Distributed Privacy-Preserving Learning Technology for distributed data analytics on medical data
– Differential Authentication Mechanisms for secure, personalised and usable authentication and authorisation
-Data Fabrication for Medical Data for generating synthetic but realistic patient record
– Data Cloaking for Medical Data for masking the data to allow safe transmission over potentially untrusted networks
– Semantic-Preserving Encryption to allow application of advanced data analytics while preserving data privacy
– Edinburgh Cancer Care Personalised Treatment will provide a patient app where cancer patients will be able to add information securely and confidentially on their symptoms between chemotherapy treatments, and clinical staff (e.g., GP or oncologist), can adapt treatment if required and improve their outcome and toxicity levels.
– Trans-National Data Exchange will focus on scenarios where information from individual use cases needs to be exchanged, transmitting data across national borders, complying with a combination of different regulations.