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All Journal International Journal of Advances in Intelligent Informatics
Azrina Md Ralib
Department of Anaesthesiology, Kulliyyah of Medicine, International Islamic University Malaysia
Computer Science & IT

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A particle swarm optimization levy flight algorithm for imputation of missing creatinine dataset Amelia Ritahani Ismail; Normaziah Abdul Aziz; Azrina Md Ralib; Nadzurah Zainal Abidin; Samar Salem Bashath
International Journal of Advances in Intelligent Informatics Vol 7, No 2 (2021): July 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v7i2.677

Abstract

Clinicians could intervene during what may be a crucial stage for preventing permanent kidney injury if patients with incipient Acute Kidney Injury (AKI) and those at high risk of developing AKI could be identified. This paper proposes an improved mechanism to machine learning imputation algorithms by introducing the Particle Swarm Levy Flight algorithm. We improve the algorithms by modifying the Particle Swarm Optimization Algorithm (PSO), by enhancing the algorithm with levy flight (PSOLF). The creatinine dataset that we collected, including AKI diagnosis and staging, mortality at hospital discharge, and renal recovery, are tested and compared with other machine learning algorithms such as Genetic Algorithm and traditional PSO. The proposed algorithms' performances are validated with a statistical significance test. The results show that SVMPSOLF has better performance than the other method. This research could be useful as an important tool of prognostic capabilities for determining which patients are likely to suffer from AKI, potentially allowing clinicians to intervene before kidney damage manifests.
Co-Authors Amelia Ritahani Ismail Nadzurah Zainal Abidin Normaziah Abdul Aziz Samar Salem Bashath