Neural network signal analysis in immunology

Fabian J. Theis, Dominic Hartl, Susanne Krauss-Etschmann, Elmar W. Lang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper aims to investigate whether both supervised and unsupervised signal analysis contributes to the interpretation of immunological data. For this purpose a data base was set up containing measured data from bronchoalveolarlavage fluid which was obtained from 37 children with pulmonary diseases. The children were dichotomized into two groups: 20 children suffered from chronic bronchitis whereas 17 children had an interstitial lung disease. A self-organizing map (SOM) was utilized to test higher-order correlations between cellular subsets and the patient groups. Furthermore, a supervised approach with a perceptron trained to the patients' diagnosis was applied. The SOM confirmed the results that were expected from previous statistical analyses and shed light on formerly not considered relationships. The supervised perceptron learning after principal component analysis for dimension reduction turned out to be highly successful by linearly separating the patients into two groups with different diagnoses. The simplicity of the perceptron made it easy to extract diagnosis rules, which partly were known already and is now readily be tested on larger data sets.

Original languageEnglish
Title of host publicationProceedings - 7th International Symposium on Signal Processing and Its Applications, ISSPA 2003
PublisherIEEE Computer Society
Pages235-238
Number of pages4
ISBN (Print)0780379462, 9780780379466
DOIs
StatePublished - 2003
Externally publishedYes
Event7th International Symposium on Signal Processing and Its Applications, ISSPA 2003 - Paris, France
Duration: 1 Jul 20034 Jul 2003

Publication series

NameProceedings - 7th International Symposium on Signal Processing and Its Applications, ISSPA 2003
Volume2

Conference

Conference7th International Symposium on Signal Processing and Its Applications, ISSPA 2003
Country/TerritoryFrance
CityParis
Period1/07/034/07/03

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