Classification of renal failure using simplified fuzzy adaptive resonance theory map.

Venkatesan, P.; Suresh, M.L.

International Journal of Computer Science and Network Security; 2009; 9; 129-134.

Abstract: Simplified Fuzzy Adaptive Resonance Theory Map (SFAM) is a family of neural networks that performs incremental supervised learning of recognition categories and multidimensional maps of both binary and analog patterns. SFAM is fast, interactive, incremental and stable and it is being applied to prediction in many areas. Medical diagnoses present many challenges in classifying patients based on symptoms. One of the major problems in medical diagnosis is the subjectivity involved in classification of diseases like renal failure. This paper discusses the usefulness of SFAM in classifying renal failure. A database containing 1200 renal failure cases are used in this work and the network model resulted in about 90% correct classification.

Keywords: Simplified Fuzzy ART Map, Medical Diagnosis

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