At the 21st edition of the Health Data and Protection Security Forum organized by the Spanish Health Informatics Society (Sociedad Española de Informática de la Salud: SEIS) and held in February, GMV presented its innovative uTile proposal to foster federated research, as participating institutions have the opportunity for federated learning, without compromising data security.

As Juan Miguel Auñón, a GMV data scientist, explained during the presentation “Security in Health Data Sharing,” in the era of artificial intelligence, “preserving people's privacy” is crucial. In the specific case of health, “it is vitally important, as, although AI may be a great help in driving great advancements in clinical and pharmaceutical research, we cannot forget that the data belong to patients and we cannot compromise their privacy.”

To guarantee that privacy, Auñón indicated that “technology offers solutions to overcome this challenge, specifically with privacy-enhancing technologies, we don’t have to choose between privacy and creating AI tools.” Thus, GMV developed the uTile product over the last five years. It is “capable of creating distributed AI models, thanks to federated training, guaranteeing patient privacy.”