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Particle swarm optimization for pap-smear diagnosis

Marinakis Ioannis, Marinaki Magdalini, Dounias, G

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URIhttp://purl.tuc.gr/dl/dias/5F20CA3D-1C95-4A91-BEFA-C2F1EF4EA6CE-
Identifierhttps://doi.org/10.1016/j.eswa.2007.08.089-
Languageen-
Extent12 pagesen
TitleParticle swarm optimization for pap-smear diagnosisen
CreatorMarinakis Ioannisen
CreatorΜαρινακης Ιωαννηςel
CreatorMarinaki Magdalinien
CreatorΜαρινακη Μαγδαληνηel
CreatorDounias, Gen
PublisherElsevieren
Content SummaryThe term pap-smear refers to samples of human cells stained by the so-called Papanicolaou method. The purpose of the Papanicolaou method is to diagnose pre-cancerous cell changes before they progress to invasive carcinoma. In this paper, a metaheuristic algorithm is proposed in order to classify the cells. Two databases are used, constructed in different times by expert Medical Doctors, consisting of 917 and 500 images of pap-smear cells, respectively. Each cell is described by 20 numerical features and the cells fall into seven classes but a minimal requirement is to separate normal from abnormal cells which is a two-class problem. For finding the best possible performing feature subset, an effective particle swarm optimization scheme is proposed. This algorithmic scheme is combined with a number of nearest neighbor based classifiers. Results show that classification accuracy generally outperforms other previously applied intelligent approaches.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-11-05-
Date of Publication2008-
SubjectPap smearen
SubjectPapanicolaou smearen
SubjectPapanicolaou testen
Subjectpap testen
Subjectpap smearen
Subjectpapanicolaou smearen
Subjectpapanicolaou testen
Bibliographic CitationY. Marinakis, M. Marinaki , G. Dounias, "Particle swarm optimization for pap-smear diagnosis, "Expert Syst.with Appl. ,vol. 35,no.4, pp.1645-1656,Nov. 2008.doi:10.1016/j.eswa.2007.08.089en

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