USING BAYESIAN METHODS IN THE TASK OF MODELING THE PATIENTS' PHARMACORESISTANCE DEVELOPMENT

Mariia A. Voronenko


Kherson National Technical University (Ukraine)
http://orcid.org/0000-0002-5392-5125

Ulzhalgas M. Zhunissova


Astana Medical University (Kazakhstan)
http://orcid.org/0000-0001-5255-9314

Saule S. Smailova


D.Serikbayev East Kazakhstan State Technical University (Kazakhstan)
http://orcid.org/0000-0002-8411-3584

Luidmila N. Lytvynenko


Kherson City Psychoneurological Clinic (Ukraine)
http://orcid.org/0000-0001-8445-5704

Nataliia B. Savina


National University of Water and Environmental Engineering (Ukraine)
http://orcid.org/0000-0001-8339-1219

Pavlo P. Mulesa


Uzhhorod National University (Ukraine)
http://orcid.org/0000-0002-3437-8082

Volodymyr I. Lytvynenko

immun56@gmail.com
Kherson National Technical University (Ukraine)
http://orcid.org/0000-0002-1536-5542

Abstract

In this paper, we propose a methodology for using static Bayesian networks (BN) in modeling the development of pharmacoresistance in patients with a diagnosis of epilepsy. Methods for constructing the structure of a static BN, their parametric training, validation, sensitivity analysis and “What-if” scenario analysis are considered. The model was designed in collaboration with expert doctors, as well as expert pharmacologists in the selection and quantification of input and output variables.


Keywords:

epileptology, pharmacoresistance, Bayesian networks, structural learning, parametric learning, sensitivity analysis, validation

Bates D. W., Kuperman G. J., Wang S., Gandhi T., Kittler A.: Ten commandments for effective clinical decision support: Making the practice of evidence-based medicine a reality. Journal of the American Medical Informatics Association 10, 2003, 523–530.
DOI: https://doi.org/10.1197/jamia.M1370   Google Scholar

Castillo E. F., Guti´errez J. M., Hadi A. S.: Sensitivity analysis in discrete Bayesian networks. IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans 27(4), 1997, 412–423.
DOI: https://doi.org/10.1109/3468.594909   Google Scholar

Cheeseman P., Kelly M., Taylor W., Freema D., Stutz J.: Bayesian classification. Proceedings of AAAI, St. Paul 1988, 607–611.
  Google Scholar

Cooper G. F.: Current research directions in the development of expert systems based on belief networks. Applied Stochastic Models and Data Analysis 5, 1989, 39–52.
DOI: https://doi.org/10.1002/asm.3150050106   Google Scholar

Darwiche A.: A differential approach to inference in Bayesian networks. Proceedings of Uncertainty in Artificial Intelligence 2000, 123–132.
  Google Scholar

Hiritis N.: Predictors of pharmacoresistant epilepsy. Epilepsy research 75(2-3), 2007, 192–196.
DOI: https://doi.org/10.1016/j.eplepsyres.2007.06.003   Google Scholar

Kahane Ph., Berg A., Loscher W.: Current knowledge on basic mechanism of drug resistance. Drug resistant epilepsy, UK John Libbey Eurotext, 2008, 47–57.
  Google Scholar

Kawamoto K., Houlihan C. A., Balas E. A., Lobach D. F.: Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. British Medical Journa 330, 2005, 765–773.
DOI: https://doi.org/10.1136/bmj.38398.500764.8F   Google Scholar

Kipersztok O., Wang H.: Another look at sensitivity of Bayesian networks to imprecise probabilities. Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics 2001, 226–232.
  Google Scholar

Kjærulff U., van der Gaag L. C.: Making sensitivity analysis computationally efficient. Proceedings of Uncertainty in Artificial Intelligence 2000, 317–325.
  Google Scholar

Kwan P., Arzimanoglou A., Berg A. T., Brodie M. J.: Definition of drug resistant epilepsy: Consensus proposal by the ad hoc Task Force of the ILAE Commission on Therapeutic Strategies. Epilepsia 51(6), 2010, 1069–1077.
DOI: https://doi.org/10.1111/j.1528-1167.2009.02397.x   Google Scholar

Lucas P. J. F., Boot H., Taal B. G.: Decision-theoretic network approach to treatment management and prognosis. Knowledge-based Systems 11, 1998, 321–330.
DOI: https://doi.org/10.1016/S0950-7051(98)00060-4   Google Scholar

Miller R.: Medical diagnostic decision support systems-past, present and future. Journal of the American Medical Informatics Association 1, 1994, 8–27.
DOI: https://doi.org/10.1136/jamia.1994.95236141   Google Scholar

Musen M. A., Shahar Y., Shortliffe E. H.: Biomedial Informatics: computer applications in health care and biomedicine. Springer, New York 2006, 698–736.
DOI: https://doi.org/10.1007/0-387-36278-9_20   Google Scholar

Osheroff J. A.: Improving medication use and outcomes with clinical decision support: a step-by-step guide. Healthcare Information and Management Systems Society, Chicago 2009.
  Google Scholar

Percell G. P.: What makes a good clinical decision support system. British Medical Journal 330, 2005, 740–741.
DOI: https://doi.org/10.1136/bmj.330.7494.740   Google Scholar

Download


Published
2022-06-30

Cited by

Voronenko, M. A., Zhunissova, U. M., Smailova, S. S., Lytvynenko, L. N., Savina, N. B., Mulesa, P. P., & Lytvynenko, V. I. (2022). USING BAYESIAN METHODS IN THE TASK OF MODELING THE PATIENTS’ PHARMACORESISTANCE DEVELOPMENT. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 12(2), 77–82. https://doi.org/10.35784/iapgos.2968

Authors

Mariia A. Voronenko 

Kherson National Technical University Ukraine
http://orcid.org/0000-0002-5392-5125

Authors

Ulzhalgas M. Zhunissova 

Astana Medical University Kazakhstan
http://orcid.org/0000-0001-5255-9314

Authors

Saule S. Smailova 

D.Serikbayev East Kazakhstan State Technical University Kazakhstan
http://orcid.org/0000-0002-8411-3584

Authors

Luidmila N. Lytvynenko 

Kherson City Psychoneurological Clinic Ukraine
http://orcid.org/0000-0001-8445-5704

Authors

Nataliia B. Savina 

National University of Water and Environmental Engineering Ukraine
http://orcid.org/0000-0001-8339-1219

Authors

Pavlo P. Mulesa 

Uzhhorod National University Ukraine
http://orcid.org/0000-0002-3437-8082

Authors

Volodymyr I. Lytvynenko 
immun56@gmail.com
Kherson National Technical University Ukraine
http://orcid.org/0000-0002-1536-5542

Statistics

Abstract views: 239
PDF downloads: 141