Two-Stage Classifier for Diagnosis of Hypertension Type

  • Michal Wozniak
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4345)


The inductive learning approach could be immensely useful as the method generating effective classifiers. This paper presents idea of constructing two-stage classifier for diagnosis of the type of hypertension (essential hypertension and five type of secondary one: fibroplastic renal artery stenosis, atheromatous renal artery stenosis, Conn’s syndrome, renal cystic disease and pheochromocystoma). The first step decides if patient suffers from essential hypertension or secondary one. This decision is made on the base on the decision of classifier obtained by boosted version of additive tree algorithm. The second step of classification decides which type of secondary hypertension patient is suffering from. The second step of classifier makes its own decision using human expert rules. The decisions of these classifiers are made only on base on blood pressure, general information and basis biochemical data.


Essential Hypertension Correct Classification Renal Artery Stenosis Classifier Ensemble Secondary Hypertension 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Michal Wozniak
    • 1
  1. 1.Chair of Systems and Computer NetworksWroclaw University of TechnologyWroclawPoland

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