A Bayesian Network and Genetic Algorithm-Based Theoretical Framework for Antibiotic Management in Clinical Settings

Huiliang Zhai, Wenyan Zhu


In this paper, we propose a novel theoretical framework to simulate antibiotic management phenomena. It is assumed that
the antibiotic management system is closed. Markov model is used to predict the trend of the share of antibiotics in the fully competitive
market. In addition, data sets of three types of drugs (antibiotics, high content of antibiotic medicines and other drugs) are selected from
questionnaire. According to Markov model, the occupancy of drugs after k years could be obtained. Other than that, the management model
is built based on Bayesian network to establish probability model for the use of antibiotics. It is necessary to use genetic algorithm to
optimize the network.


Antibiotic management system; Markov chain; Bayesian network; genetic algorithm

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DOI: https://doi.org/10.18686/esta.v10i2.407


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