The project is funded by the Ministry of Science, Innovation and Universities and by the CDTI under the “Multi-Country” Projects call linked to the Advanced Health PERTE, within the framework of the Recovery, Transformation, and Resilience Plan. The main objective is to make the most of electronic health record (EHR) data in clinical research through the use of these standards, advanced techniques such as Natural Language Processing (NLP), and knowledge graphs. As a result, the project will generate tools and methodologies that, on one hand, facilitate the structuring and normalization of narrative clinical texts, and on the other, enable the use of information contained in openEHR repositories for clinical research.

Project co-financed by IVACE and the European Union through ERDF. This project aims to develop an information retrieval system that enables semantic querying of narrative clinical documents. A document index based on the conceptual model of the SNOMED CT terminology is used, and the expression constraint language serves as the query language. To enhance search capabilities, methods are being researched and developed to evaluate the similarity of clinical documents based on graph and document embeddings, allowing the retrieval of documents and patients similar to a given one.

Project co-financed by IVACE+I and the European Union through ERDF. The main objective of this project is to develop new software tools based on virtual and augmented reality and digital twin technologies to assist neurosurgeons in planning and performing surgeries, as well as to provide training and education in a safe, simulated environment. This approach aims to reduce operating room intervention times and decrease single-use material waste, thereby minimizing the environmental impact of surgical procedures.

The Federated Artificial Intelligence Network to Accelerate Health Research (TSI-100205-2021-17) has been funded by the Ministry for Digital Transformation and Public Administration through the AI R&D Missions Program 2021, within the framework of the Spain Digital 2025 Agenda and the National Artificial Intelligence Strategy, with European funding via the Recovery, Transformation, and Resilience Plan. The main challenge of TARTAGLIA is to create an ecosystem that channels research activity and enables the development of AI tools on data in a joint and secure manner, establishing a federated network as a key factor to contribute to and benefit from data repositories. It also aims to increase professionals’ confidence by supporting decision-making in the diagnosis and treatment of Alzheimer’s, Macular Degeneration, Prostate Cancer, Complex Chronic Conditions, and Ultrasound Diagnostics, ultimately fostering a more competitive market in Spain and Europe to encourage the creation and growth of companies. Funded by the European Union – NextGenerationEU. However, the views and opinions expressed are solely those of the author(s) and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the European Commission can be held responsible for them.