euCanShare, towards a centralised, secure and sustainable platform for enhanced cross-border data sharing in cardiology

The H2020 project euCanShare, coordinated by Karim Lekhadir, euCanShare, will develop a centralised, secure and sustainable platform for enhanced cross-border data sharing and multi-study personalised medicine research in cardiology. euCanSHare's legal framework will be built through detailed ethical and legal interoperability analysis, while investigating innovative solutions for promoting responsible Open Science based on the emerging blockchain technology. In this project, DTIC-UPF will coordinate a highly experienced and multi-disciplinary consortium that includes 11 European research institutions, two European organisations, two European SMEs and three Canadian institutions. Among the research institutions, the Barcelona Supercomputing Center (BSC) and the Center for Genomic Regulation (CRG), members as DTIC-UPF of the of the SOMM Alliance of Spanish excellence centers, are involved.

Karim Lekadir gave a presentation about the project at the seminar series of the Department on February 22nd (see slides). Abstract below:

The big data revolution continues to have a transformative effect on research and innovation in a wide range of scientific and societal domains. In computer vision, for example, databases such as ImageNet now include tens of millions of images from tens of thousands of semantic categories, leading every year to important methodological advances and technological applications. However, in other domains such as in biomedicine, the promise of big data is faced with ethical/legal, operational and financial constraints, which have made it a very hard challenge to establish large-scale research databases covering multiple data types and populations. In this talk, I will first present the euCanSHare H2020 project, which aims at addressing the lack of large heterogeneous databases (including biological, imaging and clinical data), by developing the information technology tools and the data science algorithms that will enable to integrate and co-analyse multiple smaller databases, thus totalling an unprecedented 1,000,000 records. I will also describe the computational challenges and investigated solutions to enable automated and robust large-scale, multi-type and multi-cohort data analysis like never before. I will list emerging opportunities that the euCanSHare project will offer for personalised medicine and translational research. I will conclude with future perspectives in integrative data science at UPF for bypassing the long and winding road towards “true” big data in biology, medicine and beyond.


Dr Karim Lekadir is a Ramon y Cajal researcher at the Barcelona Centre for New Medical Technologies, Universitat Pompeu Fabra, Barcelona. He received a PhD in Computing from Imperial College London and was a postdoctoral researcher at Stanford University, USA. His algorithm developed during his PhD for cardiac functional quantification has been FDA/CE marked and is used in more than 250 clinical centres worldwide. He participated in several EU projects in the field of computational biomedicine, including the euHeart project for computational modelling of personalised interventions in cardiology. Through his work on statistical shape modelling using partial least squares, he finished in the first position of the MICCAI 2015 Challenge on myocardial infarct classification. His current research focuses on the development of data science, machine learning and image computing approaches for the integrative analysis of large-scale biomedical data. He is currently the Project Coordinator of the euCanSHare H2020 project (2018-2022) funded by the European Commission (6 million Euros), leading a consortium of 16 institutions to address data sharing and big data approaches in cardiovascular personalised medicine. He is an Associate Editor of the IEEE Transactions on Medical Imaging and a Guest Associate Editor on the Frontiers Special Issue on Artificial Intelligence and Cardiac Imaging.

Additional information

UPF press release