PARAMETER ESTIMATION TO AN ANEMIA MODEL USING THE PARTICLE SWARM OPTIMIZATION

The aim of this study is to predict anemia from a population through biomedical variables by using the optimum linear model. A linear medical model based on biomedical variables is produced and an effective technique is used in investigating the optimum parameters of the model. To achieve this, the particle swarm optimization (PSO) algorithm have effectively been applied in predicting the parameters of the model through the biomedical variables. The study is conducted in terms of data set consisting of 539 subjects provided from blood laboratories. Optimum values of the parameters produced from the PSO algorithm are used here to obtain the more realistic model. The model based on the variables and outcomes is expected to serve as a good indicator of disease diagnosis for health providers and planning treatment schedules for their patients. Thus, the article is believed to be beneficial especially for who are interested in biomedical models arising in various fields of medical science, especially anemia.

Keywords:

Anemia, medical model linear model, particle swarm optimization.,

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