Abstract
This paper is devoted to the problem of automated support of decision-taking process in healthcare. The theranostic process is typified as a special case of an administrative process. Correct solutions of problems in medicine are based on metering big amounts of data. These data are represented by facts from real-life experiences and numerous guidance of evidence-based healthcare. Taking into account an enormous aggregation of data for a special isolated case is possible with application of an automated decision support system based on technology of artificial neural networks or genetic algorithms.
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References
Tikhomirova, A.N., Sidorenko, E.V.: Optimization of the process of scientific and technical expertise projects in nanobiomedical technologies. Nanotechnics 1(29), 26–28 (2012)
Bushmanov, A.V., Pchelinova, Y.S.: Software development for the decision support system in traumatology. Russ. J. Biomech. 13, 95–100 (2009)
Samsonovich, A.V.: Functional possible biologically inspired by cognitive architectures. In: XVII All-Russian Scientific-Technical Conference “Neuroinformatics-2015”. National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Moscow (2015)
Ivanov, I.A., Sopov, E.A.: Self-configuring genetic algorithm for multi-objective choice problem decision. Vestnik SibGAU 1(47), 30–35 (2013)
Koroleva, S.V.: Practical aspects of the use desirable in biomedical experiments. Mod. Probl. Sci. Educ. 6 (2011)
Pichkalev, A.V.: Generalized Harrington’s desirability function for the comparative analysis of technical facilities. The Research of the Science City, pp. 25–28 (2012)
Liubushin, N.P., Brikach, G.E.: Harrington’s desirability generalized function in multiple parameter economic tasks. Econ. Anal. Theor. Practice 18(370), 2–10 (2014)
Sosukin, A.E., Verveda, A.B.: Practical aspects of using the desirability function for a psychophysiological examination of the personnel of searchand-rescue detachments, vol. 16, Preventative medicine, 24 September 2015. www.medline.ru
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This work was supported by Competitiveness Growth Program of the Federal Autonomous Educational Institution of Higher Professional Education National Research Nuclear University MEPhI (Moscow Engineering Physics Institute).
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Fomin, A., Turov, M., Matrosova, E., Tikhomirova, A. (2018). Medical Knowledge-Based Decision Support System. In: Samsonovich, A., Klimov, V. (eds) Biologically Inspired Cognitive Architectures (BICA) for Young Scientists. BICA 2017. Advances in Intelligent Systems and Computing, vol 636. Springer, Cham. https://doi.org/10.1007/978-3-319-63940-6_46
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DOI: https://doi.org/10.1007/978-3-319-63940-6_46
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