Distinguishing medical drugs from a large set of side effects using a distributed genetic algorithm on a PC cluster

Fazal Noor, Majed Alhaisoni, Mashaan A. Alshammari, Ravi P. Ramachandran

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

Abstract

A Distributed Genetic Algorithm to compute minimal reducts is presented for a novel biomedical application to distinguish 50 medical drugs from 228 side effects. The results indicate that 15 side effects are sufficient to differentiate among all the 50 drugs. In fact, any one of 4 sets of 15 side effects can be used. The Distributed Genetic Algorithm is inherently parallel, uses a variable mutation rate and is efficiently implemented on a PC cluster using 5, 10 and 20 nodes each with a Message Passing Interface. Results show that the distributed algorithm with 20 nodes uses much less computation time than two sequential methods (savings of about a factor of 5).

Original languageEnglish (US)
Title of host publication2015 IEEE International Symposium on Circuits and Systems, ISCAS 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages790-793
Number of pages4
ISBN (Electronic)9781479983919
DOIs
StatePublished - Jul 27 2015
EventIEEE International Symposium on Circuits and Systems, ISCAS 2015 - Lisbon, Portugal
Duration: May 24 2015May 27 2015

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2015-July
ISSN (Print)0271-4310

Other

OtherIEEE International Symposium on Circuits and Systems, ISCAS 2015
CountryPortugal
CityLisbon
Period5/24/155/27/15

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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