A privacy-preserving solution for using AI
A privacy-preserving solution for using AI
Publish Date: 2026-06-16 04:00:00
Source Domain: www.vttresearch.com
The Secur-e-Health project developed a concept that enables AI to be used in the treatment of cardiovascular diseases without compromising the protection of sensitive patient data.
“The study shows that AI tools can be built for healthcare in a way that respects patients’ privacy at every stage of care,” says Mika Hilvo, Research Team Leader at VTT and national coordinator of the project. “Our work brings together the secure use of data, clinical needs and modern AI methods in a way that can support better care in the future.”
“This new approach can help strengthen trust between patients, data controllers, healthcare providers and researchers. The study shows that sensitive health data can be used collaboratively, securely and in a privacy-preserving way without organisations losing control of their data,” says Gaurang Sharma, the lead author of the publication and Research Scientist at VTT.
The project created a privacy-preserving architecture for patient care. It combines secure data processing, careful consent practices, and privacy-preserving AI tools. This can support both early risk assessment and the monitoring of care for patients with cardiovascular diseases. The solution covers the entire care pathway, from the prevention of serious heart problems (primary prevention) to supporting the care of diagnosed patients (secondary prevention).
In the prevention-focused part of the work, the research team tested methods for training AI models using health data stored in different locations, without the data needing to be transferred to a single centralised location. This enables collaboration between organisations while helping to keep patient data better protected. The results showed that models trained using privacy-preserving federated learning can perform as well as models trained using traditional ma
chine learning methods.
For patients requiring continuous care, the researchers created a secure process…
