Development of the Rocket platform for collaborative clinical studies
Development of the Rocket platform for collaborative clinical studies
Development of the Rocket platform for collaborative clinical studies
Web of the Rocket Platform: https://www.upf.edu/en/web/bia/rocket
The Rocket platform is a web-based platform that was originally designed for the visualization and processing of multi-modal imaging and meta-data of cardiac patients to allow the exploration of common data by clinicians and engineers, as part of an European project (VP2HF). In the last two years, mainly due to the Maria de Maetzu UPF grant support, the Rocket platform has evolved towards a more general cloud-based architecture that builds customized and user-friendly platforms for different purposes such as benchmarking of algorithms to promote reproducible research. For instance, the Rocket platform has been successfully adapted to fulfill the requirements of the Neubias community (COST-EU project, network of European bioimage analysts), which wanted to create a platform / social network of biomaging applications, sample data, people and a benchmarking system to test algorithms in the Cloud.
The main goal of this project is to develop a secure system for user management, anonymization services, automatic deployment and distributed computing, among other technological components still missing in the platform, still needed in the Rocket platform for being used in collaborative clinical studies. Initially, there are four potential clinical use cases that could benefit from the updated Rocket platform: a) Management of family data from patients with high-risk of sudden cardiac death, in collaboration with Hospital del Mar; b) Management of multi-modal data from patients suffering arrhythmias and at high-risk of stroke, in collaboration with Hospital Clínic de Barcelona; c) Web-based tools for processing ultrasound data of large clinical trials, in collaboration with the University of Zagreb School of Medicine and Brigham and Women’s Hospital in Boston, USA; and d) Benchmarking of image processing algorithms on the UK Biobank data, in collaboration with the Queen Mary University of London, UK.