A Systemic Review on the Adoption of Particle Swarm Optimization Algorithms in Biomedical Engineering Diagnostics and Simulations

Authors

https://doi.org/10.22105/ahse.v2i1.25

Abstract

In biomedical engineering, Particle Swarm Optimization (PSO) algorithms have been increasingly adopted for diagnostics and simulations due to their ability to optimize parameters and improve the accuracy of results effectively. Despite the growing interest in the adoption of PSO algorithms in biomedical engineering, there is a lack of comprehensive understanding of their effectiveness and limitations in diagnostics and simulations. Existing studies have focused on specific applications or case studies. Still, there is a need for a systematic review to synthesize the current state of knowledge and provide insights into the potential benefits and challenges of using PSO algorithms in this context. This study adopted a systematic review comprising a rigorous methodology to identify relevant studies on adopting PSO algorithms in biomedical engineering diagnostics and simulations. A comprehensive search strategy was also developed to identify relevant literature from significant databases. The findings revealed that PSO algorithms have been successfully applied in various biomedical applications, including image processing, signal analysis, and medical image reconstruction. This study reported improvements in accuracy, efficiency, and robustness compared to traditional optimization methods, highlighting the potential of PSO algorithms in enhancing the performance of biomedical engineering systems. The findings suggest that PSO algorithms have the potential to significantly improve the accuracy and efficiency of biomedical engineering systems, but further research is needed to address the challenges and limitations associated with their implementation.

Keywords:

Particle swarm optimization, Biomedical engineering, Algorithms, Diagnostics, Simulations

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2025-01-15

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Vol. 2 No. 1 (2025): Annals of Healthcare Systems Engineering

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A Systemic Review on the Adoption of Particle Swarm Optimization Algorithms in Biomedical Engineering Diagnostics and Simulations. (2025). Annals of Healthcare Systems Engineering, 2(1), 29-43. https://doi.org/10.22105/ahse.v2i1.25