Abstract
The work contains an example of applying the rough set theory to application of support decision making - diagnose Mitochondrial Encephalomyopathies (MEM) in a child. The resulting decision support system maximally limits the indications for invasive diagnostic methods that finally decide about diagnosis. Moreover, it shortens the time necessary for making diagnosis. System has arisen using induction (machine learning from examples) – one of the methods artificial intelligence.
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References
Barkovich, A.J.: Toxic and metabolic brain disorders. In: Pediatric Neuroimaging, pp. 55–105. Raven Press Ltd, New York (1995)
Carbonell, J.: Machine learning Paradigm and Methods. MIT Press, Cambridge, MA (1989)
Chmielewski, M.R., Grzymała-Busse, J.W.: Global discretization of continuous attributes as preprocessing for machine learning. In: Lin, T.Y., Wilderberger, A.M. (eds.) Soft Computing, Simulation Councils, San Diego, pp. 294–297 (1995)
Eymard, B., Hauw, J.J.: Mitochondrial encephalomyopathies. Curr. Opin. Neurol. Neurosurg 5, 909–916 (1992)
Grzymała-Busse, J.: A New Version of the Rule Induction System LERS. Fundamenta Informaticae 31, 27–39 (1997)
Marszał, E. (ed.): Leukodystrofie i inne choroby ośrodkowego układu nerwowego z uszkodzeniem istoty białej u dzieci i młodzieży. Śla̧ska Akademia Medyczna (1998)
Matthews, P.M., Anderman, F., Silver, K., Karpati, G., Arnold, D.L.: Proton MR spectroscopic characterization of differences in regional brain metabolic abnormalities in mitochondrial encefalomyopathies. Neurology 43, 2484–2490 (1993)
Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning about Data. Kluwer, Dordecht (1991)
Tulinius, M.H., Holme, E., Kristianson, B.: Mitochondrial encephalomyopathies in childhood: 1. Biochemical and morphologic investigations. J. Pediatrics 119, 242–250 (1991)
Tulinius, M.H., Holme, E., Kristianson, B.: Mitochondrial encephalomyopathies in childhood: 2. Clinical manifestation and syndromes. J. Pediatrics 119, 251–259 (1991)
Uvebrant, P., Lanneskog, K., Hagberg, B.: The Epidiemiology of Progressive Encephalopathies in Childhood. I Live Birth Prevalence in West Sweden. Neuropediatrics 23, 209–211 (1992)
Wakulicz-Deja, A., Paszek, P.: Diagnose Progressive Encephalopathy Applying the Rough Set Theory. International Journal of Medical Informatics 46, 119–127 (1997)
Wakulicz-Deja, A., Boryczka, M., Paszek, P.: Discretization of continuous attributes on Decision System in Mitochondrial Encephalomyopathies. In: Polkowski, L., Skowron, A. (eds.) RSCTC 1998. LNCS (LNAI), vol. 1424, pp. 483–490. Springer, Heidelberg (1998)
Wakulicz-Deja, A., Paszek, P.: Applying Rough Set Theory to Multi Stage Medical Diagnosing. Fundamenta Informaticae 20, 1–22 (2003)
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Paszek, P., Wakulicz–Deja, A. (2007). Applying Rough Set Theory to Medical Diagnosing. In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds) Rough Sets and Intelligent Systems Paradigms. RSEISP 2007. Lecture Notes in Computer Science(), vol 4585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73451-2_45
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DOI: https://doi.org/10.1007/978-3-540-73451-2_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73450-5
Online ISBN: 978-3-540-73451-2
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