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

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

References

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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

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

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