Abstract
This paper presents fuzzy inference systems developed for the multistage pattern recognition. Two different methods of generating fuzzy if-then rules from empirical data are presented and their application to the computer-aided diagnosis of acute renal failure are discussed and compared with algorithms based on statistical model.
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Kurzynski, M. (2003). Fuzzy Inference Systems for Multistage Diagnosis of Acute Renal Failure in Children. In: Perner, P., Brause, R., Holzhütter, HG. (eds) Medical Data Analysis. ISMDA 2003. Lecture Notes in Computer Science, vol 2868. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39619-2_13
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DOI: https://doi.org/10.1007/978-3-540-39619-2_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20282-0
Online ISBN: 978-3-540-39619-2
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