PRIVASA -Privacy Preserving AI for Synthetic and Anonymous Health Data
Secure data exchange and storage are key features in any medical imaging system. Strict privacy preserving strategies can be a major obstacle for improving patient care through AI development. The apparent conflict between patient privacy and RDI goals is resolved by designing next-generation data analysis tools. ​​
 
PRIVASA designs and develops a data analysis framework, that allows enterprises to develop their software products on encrypted data from multiple institutions, hospitals, and clinics without sharing the patient data. ​​To achieve this, the project applies federated, secure and privacy-preserving artificial intelligence (AI). PRIVASA focuses on medical imaging applications, considering potential clinical benefits and prospects in medical imaging and beyond.​​
 
PRIVASA  consortium,  together  with  academic  and  industrial  partners,  propose  a  data-driven research, development, and innovation approach to facilitate collection and sharing of medical image data that  meets  strict  data  protection  criteria.  Project aim  to  bring  agility  and  flexibility  to  accelerate  product development of AI enterprises operating in Finland and international healthcare businesses and markets. Ultimately,  in PRIVASA  the  main motivation is  to  create  a  viable  privacy  protecting  ecosystem leveraging  a  competitive  advantage  based  upon  unique  knowledge  and  open  source  tools,  enabling participating commercial  actors and  companies to  compete  in  the  scalable  health  technology  sector –foremostly in Finland, but potentially also in EU region, United States, Asia, and developing countries.