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Algorithm for the Selection of Informative Symptoms in the Classification of Medical Data

dc.authoridNisanov, Ahram/0000-0002-5652-8977
dc.authorwosidAkhram, Nishanov/AAQ-9342-2021
dc.authorwosidRuzibaev, Ortik/AAX-2692-2021
dc.contributor.authorNishanov, A. Kh
dc.contributor.authorRuzibaev, O. B.
dc.contributor.authorChedjou, J. C.
dc.contributor.authorKyamakya, K.
dc.contributor.authorAbhiram, Kolli
dc.contributor.authorDe Silva, Perumadura
dc.contributor.authorKhasanova, M. A.
dc.contributor.otherDepartment of System and Applied Programming
dc.date.accessioned2024-12-16T16:27:52Z
dc.date.available2024-12-16T16:27:52Z
dc.date.issued2020
dc.departmentTashkent University of Information Technologiesen_US
dc.department-temp[Nishanov, A. Kh; Ruzibaev, O. B.] Tashkent Univ Informat Technol, Dept Software Engn, Informat Technol, Tashkent, Uzbekistan; [Chedjou, J. C.; Kyamakya, K.; Abhiram, Kolli; De Silva, Perumadura] Univ Klagerfurt, Transportat Informat Grp, Inst Smart Syst Technol, Klagenfurt, Austria; [Djurayev, G. P.] Tashkent Univ Informat Technol, Informat Technol Ctr, Tashkent, Uzbekistan; [Khasanova, M. A.] Tashkent Med Acad, Dept Fac & Hosp Therapy 2, Tashkent, Uzbekistanen_US
dc.descriptionNisanov, Ahram/0000-0002-5652-8977en_US
dc.description.abstractIn this paper the issues like preprocessing of medical data, reclassification of the training sets and determining the importance of classes, formation of reference tables, selection of an informative features set that differentiate between class objects, formed by medical professionals are discussed and solved. Mainly in the most studied references [5-8, 11-13] the Fisher's criterion is used to obtain solutions to problems/tasks. Also for solving problems, the algorithms for an estimate calculation as well as the related software programs are used. For all cases, algorithms and software programs are suggested. The study consists of two important steps. The first step is to build a reference table, based on the importance of the features and objects as well as their contribution to the classes [1-4, 9, 10]; the second step is concerned with the choice of the most useful characteristic features set to be investigated. This corresponds to solving the issue of selection of set of informative features from a given table, their visualization, and the determination of the contribution of the features set to the formation of classes [1-13].en_US
dc.description.woscitationindexConference Proceedings Citation Index - Science
dc.identifier.citation1
dc.identifier.doi[WOS-DOI-BELIRLENECEK-1]
dc.identifier.endpage658en_US
dc.identifier.isbn9789811223334
dc.identifier.scopusqualityN/A
dc.identifier.startpage647en_US
dc.identifier.urihttps://tuit-demo.gcris.com/handle/123456789/77
dc.identifier.volume12en_US
dc.identifier.wosWOS:000656123200078
dc.identifier.wosqualityN/A
dc.institutionauthorNishonov, Akhram
dc.language.isoenen_US
dc.publisherWorld Scientific Publ Co Pte Ltden_US
dc.relation.ispartof15th Symposium of Intelligent Systems and Knowledge Engineering (ISKE) held jointly with 14th International FLINS Conference (FLINS) -- AUG 18-21, 2020 -- Cologne, GERMANYen_US
dc.relation.ispartofseriesWorld Scientific Proceedings Series on Computer Engineering and Information Science
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFisher's Criterionen_US
dc.subjectFeature Selectionen_US
dc.subjectClassificationen_US
dc.subjectAlgorithms for an estimate calculationen_US
dc.subjectPreprocessing of medical dataen_US
dc.titleAlgorithm for the Selection of Informative Symptoms in the Classification of Medical Dataen_US
dc.typeConference Objecten_US
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscoveryae356381-5466-4bf4-9289-df6d0de463dd
relation.isOrgUnitOfPublication8f1f6343-6e28-43b7-91b4-47494eccb586
relation.isOrgUnitOfPublication.latestForDiscovery8f1f6343-6e28-43b7-91b4-47494eccb586

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