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dc.contributor.author Kupershtein, L. M. en
dc.contributor.author Martyniuk, T. B. en
dc.contributor.author Krencin, M. D. en
dc.contributor.author Kozhemiako, A. V. en
dc.contributor.author Bezsmertnyi, Yu. O. en
dc.contributor.author Bezsmertna, H. V. en
dc.contributor.author Kolimoldayev, M. en
dc.contributor.author Smolarz, A. en
dc.contributor.author Weryńska-Bieniasz, R. en
dc.contributor.author Uvaysova, S. en
dc.date.accessioned 2021-01-12T19:39:48Z
dc.date.available 2021-01-12T19:39:48Z
dc.date.issued 2017
dc.identifier.citation Neural expert decision support system for stroke diagnosis / L. M. Kupershtein, T. B. Martyniuk, M. D. Krencin [et al.] // Proc. of SPIE. Photonics Applications in Astronomy, Communications, Industry and High Energy Physics Experiments. – 2017, August 7. – Vol. 10445. – 104453I-6. en
dc.identifier.other doi: 10.1117/12.2280956
dc.identifier.uri https://dspace.vnmu.edu.ua/123456789/5040
dc.description Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments. 2017, Wilga, Poland. en
dc.description.abstract In the work the hybrid expert system for stroke diagnosis was presented. The base of expert system consists of neural network and production rules. This program can quickly and accurately set to the patient preliminary and final diagnoses, get examination and treatment plans, print data of patient, analyze statistics data and perform parameterized search for patients. en
dc.language.iso en en
dc.subject expert system en
dc.subject neural network en
dc.subject production rule en
dc.subject stroke en
dc.subject medical diagnosis en
dc.title Neural expert decision support system for stroke diagnosis en
dc.type Thesis en


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