Enhancement of sensitivity in melanoma detection using gray wolf and particle swarm optimization algorithm
The aim of the study is to evaluate the performance of Gray wolf algorithm using novel classification of normal and infected cells by comparing the Particle Swarm optimization algorithm. Methods and Materials: Sample size is calculated using Gpower software for Gray wolf and PSO algorithm and determ...
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Format: | Tagungsbericht |
Sprache: | eng |
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Zusammenfassung: | The aim of the study is to evaluate the performance of Gray wolf algorithm using novel classification of normal and infected cells by comparing the Particle Swarm optimization algorithm. Methods and Materials: Sample size is calculated using Gpower software for Gray wolf and PSO algorithm and determined to be 100 (power-0.8 and alpha - 0.05). Results: GWO algorithm has achieved sensitivity of 95 % compared to PSO algorithm of 85 %. The statistical t test significance between two groups is 0.02 (p |
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ISSN: | 0094-243X 1551-7616 |
DOI: | 10.1063/5.0173289 |