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Date of Award
2015
Rights
Access perpetually restricted to EWU users with an active EWU NetID
Document Type
Thesis: EWU Only
Degree Name
Master of Science (MS) in Computer Science
Department
Computer Science
Abstract
"Medicine is an essential part of many people's health and wellbeing . However, drugs sometimes cause symptoms, many of which have yet to be associated to a drug or combination of drugs. Mining patient data allows unknown associations between drugs and symptoms to be discovered. General-purpose GPU computing is the next evolution in processing architectures; utilization of this massively parallel processor towards drug data mining will accelerate the research and discovery of drug-symptom associations that will save money and lives"--Leaf iv.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Scholer, Jesse, "Multi-drug association rule mining on graphics processing unit" (2015). EWU Masters Thesis Collection. 309.
https://dc.ewu.edu/theses/309
