Assessment of nodal involvement and survival analysis in breast cancer patients using image cytometric data: statistical, neural network and fuzzy approaches

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dc.contributor.authorSeker, H.en
dc.contributor.authorNaguib, R. N. G.en
dc.contributor.authorOdetayo, M. O.en
dc.contributor.authorPetrovic, D.en
dc.date.accessioned2008-11-24T13:24:12Z
dc.date.available2008-11-24T13:24:12Z
dc.date.issued2002-01-01en
dc.descriptionThis paper is concerned with prognostic decision making in the breast cancer field and presents the development of a framework based on a multiple-method strategy. Different sets of biomarkers that were likely to be associated with breast cancer prognosis were analysed for the first time and then the results that have been used by the research community were produced. The paper has been widely accepted and recently been flagged up in a review paper published in “Cancer Informatics” (2:59-78,2006) as one of the useful and recommended to read papers (“papers of good general interest or relevance”) in the field.en
dc.identifier.citationSeker, H. et al. (2002) Assessment of nodal involvement and survival analysis in breast cancer patients using image cytometric data: statistical, neural network and fuzzy approaches. Anticancer Research: International Journal of Cancer Research and Treatment, 22(1), pp. 433-438.
dc.identifier.issn0250-7005en
dc.identifier.urihttp://hdl.handle.net/2086/176
dc.language.isoenen
dc.publisherIIARen
dc.researchgroupCentre for Computational Intelligence
dc.researchgroupPharmaceutical Technologies
dc.subjectRAE 2008
dc.subjectUoA 23 Computer Science and Informatics
dc.subjectfuzzy algorithm
dc.subjectprognosis
dc.subjectmalignant lymphadenopathy
dc.subjectlymph node
dc.titleAssessment of nodal involvement and survival analysis in breast cancer patients using image cytometric data: statistical, neural network and fuzzy approachesen
dc.typeArticleen

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