Prediction of anemia with a particle swarm optimization-based approach




Anemia, Particle Swarm Optimization, Support Vector Machine, Prediction


Healthcare enables the maintenance of health through some physical and mental care for the prevention, diagnosis and treatment of disease. Diagnosis of anemia, one of the most common health problems of the age, is also very ambitious. Whereas, pathological individuals could be predicted through various biomedical variables using some appropriate methods. In order to estimate these individuals just by taking into account biological data, particle swarm optimization (PSO) and support vector machine (SVM) clustering techniques have been merged (PSO-SVM). In this respect, the dataset provided has been divided into five clusters based on anemia types consisting of 539 subjects in total, and the anemia values of each subject have been recorded according to corresponding biomedical variables taken as independent parameters. The findings of the PSO-SVM method have been compared to the results of the SVM algorithm. The hybrid PSO-SVM method has proven to be quite effective, particularly in terms of the high predictability of clustered disease types. it is possible to lead the successful creation of appropriate treatment programs for diagnosed patients without overlooking or wasting time during treatment.


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Author Biographies

Arshed A. Ahmad, Department of Computer Science, University of Diyala, Iraq

Arshed A. Ahmad born in Iraq in 1980. He is an Assistant Professor at the University of Diyala, Iraq. He received a Ph.D. degree from Yildiz Technical University in 2020. His research interests include mathematical modeling, applied mathematics, numerical analysis, and probability and statistics. He is the author of more than 14 research papers since 2008.

Khalid M. Saffer , Department of Computer Science, University of Diyala, Iraq

Khalid M. Saffer born in Iraq in 1971. He is a lecturer at the University of Diyala, Iraq. He received a Ph.D. degree from Altinbas University in 2018. His research interests include optimization algorithms, information technology, image processing, information security, and database systems design and implementation. He is the author of more than 12 research papers since 2011.

Murat Sari, Department of Mathematical Engineering, Istanbul Technical University, Istanbul, Turkey

Murat Sari is a Professor of the Department of Mathematical Engineering at Istanbul Technical University. He completed his Ph.D. in Mathematics from the University of South Wales, UK, in 2000. His current research interests include artificial intelligence modeling, simulation and computational methods, computational fluid dynamics, modeling of nonlinear behaviors, economical modeling, and biomechanical/biomedical modeling. He has about 100 high-quality scientific papers, over 50 conference proceedings, and has written various chapters in some books. He is a reviewer/editor for some international high-quality journals.

Hande Uslu, Department of Mathematics, Yildiz Technical University, Istanbul, Turkey

Hande Uslu is a Research Assistant in the Department of Mathematics at Yildiz Technical University, Istanbul, Turkey since 2017. She received her B.Sc degree in Mathematics from Bogazici University in 2015, and MSc degree in Applied Mathematics from Yildiz Technical University, in 2018. She is currently pursuing her Ph.D. studies in the thesis period in the Department of Mathematics at Yildiz Technical University. Her research interests are mathematical modeling, simulation techniques, stochastic processes, and artificial intelligence. She has six scientific papers and more than fifteen conference proceedings.


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DOI: 10.11121/ijocta.2023.1269
Published: 2023-07-28

How to Cite

Ahmad, A. A. ., Saffer , K. M., Sari, M., & Uslu, H. (2023). Prediction of anemia with a particle swarm optimization-based approach. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 13(2), 214–223.



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