A Novel Approach of Determining the Risks for the Development of Hyperinsulinemia in the Children and Adolescent Population Using Radial Basis Function and Support Vector Machine Learning Algorithm.

Lukic, Igor; Rankovic, Nevena; Savic, Nikola; Rankovic, Dragica; Popov, Zeljko; Vujic, Ana; Folic, Nevena

Lukic, Igor; Rankovic, Nevena; Savic, Nikola; Rankovic, Dragica; Popov, Zeljko; Vujic, Ana; Folic, Nevena.

Afiliação

Lukic I; Faculty of Medical Sciences, University of Kragujevac, 34000 Kragujevac, Serbia.
Rankovic N; Department of Computer Science, School of Computing, Union University, 11000 Belgrade, Serbia.
Savic N; Faculty of Health and Business Studies, Singidunum University, 14000 Valjevo, Serbia.
Rankovic D; Department of Mathematics and Statistics, Faculty of Applied Sciences in Nis, Union University "Nikola Tesla", 18000 Nis, Serbia.
Popov Z; School Center with Dormitory "Dositej Obradovic", 24000 Subotica, Serbia.
Vujic A; Faculty of Medical Sciences, University of Kragujevac, 34000 Kragujevac, Serbia.
Folic N; Faculty of Medical Sciences, University of Kragujevac, 34000 Kragujevac, Serbia.

Healthcare (Basel) ; 10(5)2022 May 17.

Article em En | MEDLINE | ID: mdl-35628058

Palavras-chave

SVM; children and adolescents; glucose; hyperinsulinemia; insulin; risk factors

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Healthcare (Basel) Ano de publicação: 2022 Tipo de documento: Article

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