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PARAMETER ESTIMATION TO AN ANEMIA MODEL USING THE PARTICLE SWARM OPTIMIZATION

Year 2019, Volume: 37 Issue: 4, 1335 - 1347, 01.12.2019

Abstract

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.

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There are 47 citations in total.

Details

Primary Language English
Journal Section Research Articles
Authors

Arshed A. Ahmad This is me 0000-0003-1393-1253

Murat Sarı This is me 0000-0003-0508-2917

Publication Date December 1, 2019
Submission Date March 9, 2019
Published in Issue Year 2019 Volume: 37 Issue: 4

Cite

Vancouver Ahmad AA, Sarı M. PARAMETER ESTIMATION TO AN ANEMIA MODEL USING THE PARTICLE SWARM OPTIMIZATION. SIGMA. 2019;37(4):1335-47.

IMPORTANT NOTE: JOURNAL SUBMISSION LINK https://eds.yildiz.edu.tr/sigma/