Conference Proceeding

Weighted fuzzy classification with integrated learning method for medical diagnosis

Coll. of Eng., Osaka Prefecture Univ.
02/2006; DOI:10.1109/IEMBS.2005.1615761 pp.5623 - 5626 In proceeding of: Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Source: IEEE Xplore

ABSTRACT Medical diagnosis can be viewed as a pattern classification problem: based a set of input features the goal is to classify a patient as having a particular disorder or as not having it. Performance of medical diagnosis is typically assessed in terms of sensitivity and specificity. In this paper we introduce a pattern classification system for medical diagnosis that is based on fuzzy logic and utilises weighted training patterns. Adjusting the weights allows to focus either on sensitivity or specificity while not neglecting the other one and hence lends a degree of flexibility to the diagnostic process. A learning method is utilised that provides improved classification performance. Excellent classification results based on the University of Wisconsin breast cancer database are presented

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Keywords

classification performance
 
classify
 
diagnostic process
 
fuzzy logic
 
learning method
 
particular disorder
 
pattern classification problem
 
pattern classification system
 
utilises weighted training patterns
 
Wisconsin breast cancer database
 

T Nakashima