NDLI: SVM ensemble classification of nmr spectra based on different configurations of data processing techniques

Content Provider	IEEE Xplore Digital Library
Author	Lienemann, K. Plotz, T. Fink, G.A.
Copyright Year	2008
Description	Author affiliation: Dortmund Univ. of Technol., Dortmund (Lienemann, K.; Plotz, T.; Fink, G.A.)
Abstract	The early detection of drug-induced organ toxicities is one of the major goals in safety pharmacology. Automating this process by classification of metabolic changes based on the analysis of $^{1}H$ nuclear magnetic resonance spectra improves this process. In this paper we propose an ensemble classification system based on support vector machines trained on diverse ldquoviewsrdquo on the data. These views are created by variation of preprocessing techniques and the final classification is achieved by voting on an optimized selection of all experts. Results of an experimental evaluation on a challenging data-set from industrial safety pharmacology show the effectiveness of the proposed approach w.r.t. the detection of drug-induced toxicity.
Starting Page	1
Ending Page	4
File Size	261023
Page Count	4
File Format	PDF
ISBN	9781424421749
ISSN	10514651
DOI	10.1109/ICPR.2008.4761761
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Support vector machine classification Nuclear magnetic resonance Data processing Safety Magnetic analysis Drugs Pharmaceutical technology Voting Spectroscopy
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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