In BCN-MEDTECH we are committed to transfer our technology and the knowledge derived from it to clinicians. We work towards the obtention of results that are fully clinically-interpretable. Indeed, human interpretability is increasingly recognized as a highly relevant feature of data analysis methodologies, crucial in efforts towards data-driven precision medicine, which is based on informed and auditable decisions.


We spend a significant amount of time talking to specialist, to have a deeper understanding of the clinical problems that we tackle.

Some of our projects consist in analyzing heterogeneous biomedical data using machine learning techniques for diagnosis, severity estimation, and prediction of adverse events. However, to be able to extract reliable and relevant conclusions from our machine learning research, we need to work with large collections of data, ideally above 1000 cases. To this end, we collaborate with clinical centers that coordinate some of the most important cardiology trials performed to date.