An optimization approach to identify the relationship between features and output of a multi-label classifier Mammadov, Musa, Rubinov, Alex and Yearwood, John Leighton 2007, An optimization approach to identify the relationship between features and output of a multi-label classifier. In Pardalos, Panos M., Boginski, Vladimir L. and Vazacopoulos, Alkis (ed), Data Mining in Biomedicine, Springer, Boston, Mass., pp.141-167, doi: 10.1007/978-0-387-69319-4_9. Title An optimization approach to identify the relationship between features and output of a multi-label classifier Author(s) Mammadov, Musa orcid.org/0000-0002-2600-3379 Rubinov, Alex Yearwood, John Leighton orcid.org/0000-0002-7562-6767 Title of book Data Mining in Biomedicine Editor(s) Pardalos, Panos M. Boginski, Vladimir L. Vazacopoulos, Alkis Publication date 2007 Series Springer Optimization and Its Applications Book Series (SOIA) Chapter number 9 Total chapters 28 Start page 141 End page 167 Total pages 27 Publisher Springer Place of Publication Boston, Mass. Keyword(s) knowledge representation adverse drug reaction text categorization multi-label classification suspected drugs Summary Multi-label classification is an important and difficult problem that frequently arises in text categorization. The accurate identification of drugs which are responsible for reactions that have occurred is one of the important problems of adverse drug reactions (ADR). In this chapter we consider the similarities of these two problems and analyze the usefulness of drug reaction relationships for the prediction of possible reactions that may occur. We also introduce a new method for the determination of responsibility for subsets of drug(s), out of all drugs taken by a particular patient, in reactions that have been observed. This method is applied for the evaluation of the level of correctness of suspected drugs reported in Cardiovascular type reactions in the ADRAC database. The problem of interaction of drugs is also considered. ISBN 9780387693187 ISSN 1931-6828 1931-6836 Language eng DOI 10.1007/978-0-387-69319-4_9 Indigenous content off HERDC Research category B1.1 Book chapter Copyright notice ©2007, Springer Science+Business Media Persistent URL http://hdl.handle.net/10536/DRO/DU:30126033 Document type: Book Chapter Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Mon, 15 Jul 2019, 12:49:11 EST Tue, 16 Jul 2019, 05:02:36 EST Tue, 16 Jul 2019, 06:04:18 EST Fri, 06 Nov 2020, 07:54:10 EST Fri, 06 Nov 2020, 07:56:44 EST Fri, 06 Nov 2020, 10:30:52 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 3 times in Scopus Search Google Scholar Access Statistics: 35 Abstract Views  -  Detailed Statistics Created: Mon, 15 Jul 2019, 12:49:11 EST

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