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An optimization approach to identify the relationship between features and output of a multi-label classifier
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posted on 2007-01-01, 00:00 authored by Musa MammadovMusa Mammadov, Alex Rubinov, John YearwoodJohn YearwoodMulti-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.
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Title of book
Data Mining in BiomedicineVolume
7Series
Springer Optimization and Its Applications Book Series (SOIA)Chapter number
9Pagination
141 - 167Publisher
SpringerPlace of publication
Boston, Mass.Publisher DOI
ISSN
1931-6828eISSN
1931-6836ISBN-13
9780387693187Language
engPublication classification
B1.1 Book chapterCopyright notice
2007, Springer Science+Business MediaExtent
28Editor/Contributor(s)
Panos Pardalos, Vladimir Boginski, Alkis VazacopoulosUsage metrics
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