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<record>
  <title>Decision Support System for Histopathological Diagnosis of HER2 Breast Cancer using Pawlakâ€™s Information System and Mamadani Type Fuzzy Control</title>
  <journal>Journal of Intelligent Computing</journal>
  <author>Martin Tabakov, Krzysztof Rodak, Marzenna Podhorska-Okolow, Bartosz Pula, Jedrzej Grzegrzolka</author>
  <volume>4</volume>
  <issue>1</issue>
  <year>2013</year>
  <doi></doi>
  <url>http://www.dline.info/jic/fulltext/v4n1/5.pdf</url>
  <abstract>In this article, the specification of a histopathology decision making support system, based on Pawlakâ€™s information system concept and Mamdani type fuzzy control is presented. The proposed system supports the recognition process of HER-2/neu histopathology preparations through microscopy image information analysis. We used Pawlakâ€™s information system to identify the decisive set of features and the optimal set of decision rules under the considered histopathology problem. Then, the so generated decision rules were transformed into fuzzy rules and exploited in Mamdani reasoning. The proposed approach was tested over real clinical data of HER-2/neu breast cancer histopathology images.</abstract>
</record>
