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Using CHAID Algorithm in Low-Risk Metabolic Syndrome Patients

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dc.contributor.author FELEA, M. G.
dc.contributor.author FELEA, V.
dc.contributor.author GAVRILESCU, C. M.
dc.date.accessioned 2020-05-19T08:29:32Z
dc.date.available 2020-05-19T08:29:32Z
dc.date.issued 2015
dc.identifier.citation FELEA, M. G., FELEA, V., GAVRILESCU, C. M. Using CHAID Algorithm in Low-Risk Metabolic Syndrome Patients. In: ICNMBE: International conference on Nanotechnologies and Biomedical Engineering: proc. of the 3rd intern. conf., Sept. 23-26 : Program & Abstract Book , 2015. Chişinău, 2015, p. 109. en_US
dc.identifier.uri https://doi.org/10.1007/978-981-287-736-9_110
dc.identifier.uri http://repository.utm.md/handle/5014/8272
dc.description Access full text - https://doi.org/10.1007/978-981-287-736-9_110 en_US
dc.description.abstract Metabolic Syndrome (MetS), a cluster of more than three cardio-metabolic risk factors, is becoming a major worldwide health problem. CHAID analysis can bring to front the role of pathogenesis – represented by insulin resistance and measured by Reaven index, and the importance of two-cumulated criteria – as the association of hypertension and obesity, in revealing the likelihood of developing MetS in patients that do not yet account for all condition criteria. The aim of our research was to stress the order of influence of a specific two-cumulated criterion comparative to other MetS criteria comprised into a pathogenic index – the Reaven index (comprising TG and HDL that are two independent MetS diagnosis criterion). CHAID Decision Tree Algorithm can become an intelligent system to support wise decision-making and to predict the likelihood of developing MetS in patients at low-risk for this condition. en_US
dc.language.iso en en_US
dc.publisher Tehnica UTM en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject metabolic syndrome en_US
dc.subject insulin resistance en_US
dc.subject elderly two-cumulated criterion en_US
dc.title Using CHAID Algorithm in Low-Risk Metabolic Syndrome Patients en_US
dc.type Article en_US


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