Advances in Computational Immunology

dc.contributor.authorPappalardo, Francesco
dc.contributor.authorBrusic, Vladimir
dc.contributor.authorPennisi, Marzio
dc.contributor.authorZhang, Guanglan
dc.date.accessioned2017-11-15T04:36:25Z
dc.date.available2017-11-15T04:36:25Z
dc.date.issued2015
dc.description.abstractIn the paper contributed by C.-M. Svensson et al., the authors investigate the interobserver variability of image data comprising fluorescently stained circulating tumor cells and its effect on the performance of two automated classifiers, a random forest and a support vector machine. They found that uncertainty in annotation between observers limited the performance of the automated classifiers, especially when it was included in the test set on which classifier performance was measured.
dc.identifier.citationPappalardo Francesco et al.(>3), 2015, Advances in Computational Immunology, Journal of Immunology Research, 2015, Volume 2015, 3 pagesru_RU
dc.identifier.urihttp://dx.doi.org/10.1155/2015/170920
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/2820
dc.language.isoenru_RU
dc.publisherJournal of Immunology Researchru_RU
dc.rightsOpen Access - the content is available to the general publicru_RU
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectimmunologyru_RU
dc.subjectW. Schreinerru_RU
dc.subjectmolecular dynamicsru_RU
dc.subjectResearch Subject Categories::NATURAL SCIENCES::Biology::Cell and molecular biology::Immunologyru_RU
dc.titleAdvances in Computational Immunologyru_RU
dc.typeArticleru_RU

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