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dc.contributor.authorALLAHVERDİ, NOVRUZ
dc.contributor.authorALTUN, ALPASLAN
dc.contributor.authorTAGHIYEV, ANAR
dc.date.accessioned2019-07-09T14:10:06Z
dc.date.available2019-07-09T14:10:06Z
dc.date.issued2019-06
dc.identifier.issn1454-8658
dc.identifier.urihttps://hdl.handle.net/20.500.12498/938
dc.description.abstractIn this study, the effects of blood glucose levels on hemoglobin A1c (HbA1c) were investigated. For this reason, а classification model was developed by carrying out a logistic regression analysis based on machine learning and data mining methods. The purpose of using logistic regression analysis in this study was to establish a method of creating a statistical model that is most suitable and reasonable for determining the relationship between dependent and independent variables. This model shows how effective the factors that cause an increase in the HbA1c level. It can be planned to verify this method on more Electronic Heath Records databases to address the learning method of information in the local health sector with the help of data mining and machine learning methods and different clinical problems for future work.en_US
dc.language.isoen_USen_US
dc.publisherCEAIen_US
dc.titleA Machine Learning Framework to Identify the Causes of HbA1c in Patients With Type 2 Diabetes Mellitusen_US
dc.typeArticleen_US


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