Developing on-demand secure high-performance computing services for biomedical data analytics

Nicholas Robison, Nicholas Anderson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a technical and process model to support biomedical researchers requiring on-demand high performance computing on potentially sensitive medical datasets. Our approach describes the use of cost-effective, secure and scalable techniques for processing medical information via protected and encrypted computing clusters within a model High Performance Computing (HPC) environment. The process model supports an investigator defined data analytics platform capable of accepting secure data migration from local clinical research data silos into a dedicated analytic environment, and secure environment cleanup upon completion. We define metrics to support the evaluation of this pilot model through performance and stability tests, and describe evaluation of its suitability towards enabling rapid deployment by individual investigators.

Original languageEnglish (US)
Title of host publicationStudies in Health Technology and Informatics
Pages1144
Number of pages1
Volume192
Edition1-2
DOIs
StatePublished - 2013
Externally publishedYes
Event14th World Congress on Medical and Health Informatics, MEDINFO 2013 - Copenhagen, Denmark
Duration: Aug 20 2013Aug 23 2013

Other

Other14th World Congress on Medical and Health Informatics, MEDINFO 2013
CountryDenmark
CityCopenhagen
Period8/20/138/23/13

Keywords

  • Data Security
  • High Performance Computing
  • Patient Data Privacy

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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