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004.891.3:61 (13) |
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SM ISO690:2012 UMAMAHESWARI, S., BIRNICA, Y., BOOBALAN, J., AKSHAYA, V. S.. Optimizing Cervical Cancer Classification with SVM and Improved Genetic Algorithm on Pap Smear Images. In: Computer Science Journal of Moldova, 2024, vol. 32, nr. 1(94), pp. 61-83. ISSN 1561-4042. DOI: https://doi.org/10.56415/csjm.v32.05 |
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Computer Science Journal of Moldova | ||||||
Volumul 32, Numărul 1(94) / 2024 / ISSN 1561-4042 /ISSNe 2587-4330 | ||||||
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DOI:https://doi.org/10.56415/csjm.v32.05 | ||||||
CZU: 004.891.3:61 | ||||||
Pag. 61-83 | ||||||
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This study presents an approach to optimize cervical cancer classification using Support Vector Machines (SVM) and an improved Genetic Algorithm (GA) on Pap smear images. The proposed methodology involves preprocessing the images, extracting relevant features, and employing a genetic algorithm for feature selection. An SVM classifier is trained using the selected features and optimized using the genetic algorithm. The performance of the optimized model is evaluated, demonstrating improved accuracy and efficiency in cervical cancer classification. The findings hold the potential for assisting healthcare professionals in early cervical cancer diagnosis based on Pap smear images. |
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Cuvinte-cheie SVM, Pap smear images, cervical cancer, Ga, healthcare |
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