Privacy-preserving AI for Synthetic and Anonymous Health Data

PRIVASA boosts data-driven research, development and innovation by making it easier to access and share health data without compromising individuals' privacy. The core aim of the project is to add flexibility in the way that health data can be utilized in various stages of research and product development. This aim extends beyond technical solutions, as it also requires trust-building between owners, holders and users of data. Transparency, legal aspects and ethics are the cross-cutting themes to be explored throughout the multidisciplinary project.

PRIVASA develops data processing tools that apply latest AI methods to support growth of Finnish health technology business in the global data. Privacy-preserving algorithms convert sensitive data into a format that serves medical research, testing and validation with data protection guarantees. The use of anonymous data simplifies and speeds up the development cycles, as well as creates new business opportunities.

The project acknowledges the divers forms of health data developing solutions for free from patient records and biomedical images in addition to purely numerical datasets. PRIVASA offers explainable AI solutions that can be implemented as database interfaces or stand-alone services.