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Sulkava, M. and Hollmén, J. (2003) Finding profiles of forest nutrition by clustering of the self-organizing map. Proceedings of the Workshop on Self-Organizing Maps, Kitakyushu, 243-248.

has been cited by the following article:

• TITLE: Helicobacter pylori microbe and detecting with data mining algorithms

  AUTHORS: Amir Hossein Rasekh, Zeinab Liaghat, Alireza Tabebordbar

  KEYWORDS: Data Mining; Helicobacter pylori; Regression; RBF Network; Part

  JOURNAL NAME: Open Journal of Gastroenterology, Vol.3 No.2, May 28, 2013

  ABSTRACT: Nowadays medicines believe that the only definite method to diagnose the existence of Helicobacter pylori microbe is performing endoscope, however it’s painful and insufferable for young children. Thus in this paper we used data mining algorithms to diagnose the existence of this microbe and eventually we succeeded in predicting the existence of this bacterium in stomach that guides medicines to perform Endoscopy just in cases where percentage of finding this bacterium is high.