Marco Trincavelli, Silvia Coradeschi, Amy Loutfi, Bo Söderquist and Per Thunberg
Direct Identification of Bacteria in Blood Culture Samples using an Electronic Nose
IEEE Transactions on Biomedical Engineering, Volume 57, Issue 12, 10 May 2010, pp. 2884 - 2890.
Abstract: In this work we introduce a method for identification of bacteria in human blood culture samples using an electronic nose. The method uses features which capture the static (steady state) and dynamic (transient) properties of the signal from the gas sensor array and proposes a means to ensemble results from consecutive samples. The underlying mechanism for ensembling is based on an estimation of posterior probability which is extracted from a support vector machine classifier. A large data set representing 10 different bacteria cultures has been used to validate the presented methods. The results detail the performance of the proposed algorithm and show that through ensembling decisions on consecutive samples significant reliability in classification accuracy can be achieved.
Keywords: Bacteria Identification , Electronic Nose , Sepsis.
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@ARTICLE{Trincavelli_etal:TBME:2010,
  AUTHOR = {Trincavelli, Marco and Coradeschi, Silvia and Loutfi, Amy and Soederquist, Bo and Thunberg, Per},
  TITLE = {Direct Identification of Bacteria in Blood Culture Samples using an Electronic Nose},
  JOURNAL = {Biomedical Engineering, IEEE Transactions on},
  YEAR = {2010},
  VOLUME = {57},
  NUMBER = {12},
  PAGES = {2884 - 2890}
  DOI = {10.1109/TBME.2010.2049492}
}