de Vila, MH, Attar, R, Pereanez, M et al. (1 more author) (2019) MULTI-X, a State-of-the-Art Cloud-Based Ecosystem for Biomedical Research. In: 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 2018 IEEE (BIBM), 03-06 Dec 2018, Madrid, Spain. IEEE , pp. 1726-1733. ISBN 978-1-5386-5488-0
Abstract
With the exponential growth of clinical data, and the fast development of AI technologies, researchers are facing unprecedented challenges in managing data storage, scalable processing, and analysis capabilities for heterogeneous multisourced datasets. Beyond the complexity of executing data-intensive workflows over large-scale distributed data, the reproducibility of computed results is of paramount importance to validate scientific discoveries. In this paper, we present MULTIX, a cross-domain research-oriented platform, designed for collaborative and reproducible science. This cloud-based framework simplifies the logistical challenges of implementing data analytics and AI solutions by providing pre-configured environments with ad-hoc scalable computing resources and secure distributed storage, to efficiently build, test, share and reproduce scientific pipelines. An exemplary use-case in the area of cardiac image analysis will be presented together with the practical application of the platform for the analysis of ~20.000 subjects of the UK-Biobank database.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | ©2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | biomedical informatics; precision medicine; cloud computing; population analysis |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EU - European Union 765413 EPSRC EP/N026993/1 EPSRC EP/N026993/1 EPSRC EP/M006328/2 |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Mar 2019 13:16 |
Last Modified: | 05 Mar 2019 15:04 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/BIBM.2018.8621317 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:143253 |