Rapid Calculation of Medication Adherence Using Parallel Computing with R and Python

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dc.contributor.authorDavis, Nicholas
dc.date.accessioned2015-08-16T21:02:01Z
dc.date.available2015-08-16T21:02:01Z
dc.date.issued2014-09-24
dc.descriptionNick Davis, PhD Assistant Professor of Research Department of Medical Informatics University of Oklahoma, Tulsa School of Community Medicine nicholas-davis@ouhsc.edu@argoneus Oklahoma Supercomputing Symposium 2014 September 24, 2014en_US
dc.description.abstract____R and Python (with Pandas) are excellent languages for data analysis ____Parallelizing code is often trivial, with some caveats ____Faster runtimes lead to richer exploration of the dataen_US
dc.description.peerreviewNoen_US
dc.description.sponsorshipUniversity of Oklahoma OU Supercomputing Center for Education & Research (OSCER) Department of Medical Informatics, University of Oklahoma, Tulsa, School of Community Medicineen_US
dc.identifier.urihttp://hdl.handle.net/11244/15507
dc.languageen_USen_US
dc.subjectcomputer scienceen_US
dc.subjectBiology, Bioinformatics.en_US
dc.titleRapid Calculation of Medication Adherence Using Parallel Computing with R and Pythonen_US
dc.typePresentationen_US
ou.groupOklahoma Supercomputing::Oklahoma Supercomputing Symposium::2014en_US

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