dc.contributorInformática
dc.creatorBoujdad, Fatima-Zahra
dc.creatorGaignard, Alban
dc.creatorSüdholt, Mario
dc.creatorGarzón-Alfonso, Wilmer
dc.creatorBenavides Navarro, Luis Daniel
dc.creatorRedon, Richard
dc.date.accessioned2021-11-04T16:15:06Z
dc.date.accessioned2022-09-29T14:32:55Z
dc.date.available2021-11-04T16:15:06Z
dc.date.available2022-09-29T14:32:55Z
dc.date.created2021-11-04T16:15:06Z
dc.date.issued2019
dc.identifier9781728109121
dc.identifierhttps://repositorio.escuelaing.edu.co/handle/001/1797
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3774855
dc.description.abstractCooperation of research groups is nowadays common for the development and execution of biomedical analyses. Multiple partners contribute data in this context, data that is often centralized for processing at some cluster-based or supercomputer-based infrastructure. In contrast, real distributed collaboration that involves processing of data from several partners at different sites is rare. However, such distributed analyses are often very interesting, in particular, for scalability, security and privacy reasons. In this article, we motivate the need for real distributed biomedical analyses in the context of several ongoing projects, including the ICAN project that involves 34 French hospitals and affiliated research groups. We present a set of distributed architectures for such analyses that we have derived from discussions with different medical research groups and a study of related work. These architectures allow for scalability, security/privacy and reproducibility issues to be taken into account. Finally, we illustrate that these architectures can serve as the basis of a development method for biomedical distributed analyses.
dc.description.abstractLa cooperación de grupos de investigación es hoy en día común para el desarrollo y ejecución de análisis biomédicos. Múltiples socios aportan datos en este contexto, datos que a menudo se centralizan para su procesamiento en alguna infraestructura basada en clústeres o basada en supercomputadoras. Por el contrario, la colaboración distribuida real que involucra el procesamiento de datos de varios socios en diferentes sitios es rara. Sin embargo, tales análisis distribuidos suelen ser muy interesantes, en particular, por razones de escalabilidad, seguridad y privacidad. En este artículo, motivamos la necesidad de análisis biomédicos distribuidos reales en el contexto de varios proyectos en curso, incluido el proyecto ICAN que involucra a 34 hospitales franceses y grupos de investigación afiliados. Presentamos un conjunto de arquitecturas distribuidas para tales análisis que hemos derivado de discusiones con diferentes grupos de investigación médica y un estudio de trabajo relacionado. Estas arquitecturas permiten tener en cuenta cuestiones de escalabilidad, seguridad/privacidad y reproducibilidad. Finalmente, ilustramos que estas arquitecturas pueden servir como base de un método de desarrollo para análisis biomédicos distribuidos.
dc.languageeng
dc.publisherIEEE Xplore
dc.publisherLarnaca, Cyprus
dc.relation14-17 May 2019
dc.relationLarnaca, Cyprus.
dc.relationN/A
dc.relation2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)
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dc.rightshttps://creativecommons.org/licenses/by/4.0/
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.rightsAtribución 4.0 Internacional (CC BY 4.0)
dc.titleOn Distributed Collaboration for Biomedical Analyses
dc.typeDocumento de Conferencia


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