A Machine Learning Framework to Identify the Causes of HbA1c in Patients With Type 2 Diabetes Mellitus

  • Yazar/lar ALLAHVERDİ, Novruz
    ALTUN, Alpaslan
    TAGHIYEV, Anar
  • Yayın Türü Makale
  • Yayın Tarihi 2019
  • Yayıncı CEAI
  • Tek Biçim Adres https://hdl.handle.net/20.500.12498/938

In 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.

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Eser Adı
(dc.title)
A Machine Learning Framework to Identify the Causes of HbA1c in Patients With Type 2 Diabetes Mellitus
Yayın Türü
(dc.type)
Makale
Yazar/lar
(dc.contributor.author)
ALLAHVERDİ, Novruz
Yazar/lar
(dc.contributor.author)
ALTUN, Alpaslan
Yazar/lar
(dc.contributor.author)
TAGHIYEV, Anar
Atıf Dizini
(dc.source.database)
Wos
Atıf Dizini
(dc.source.database)
Scopus
Yayıncı
(dc.publisher)
CEAI
Yayın Tarihi
(dc.date.issued)
2019
Kayıt Giriş Tarihi
(dc.date.accessioned)
2019-07-09T14:10:06Z
Açık Erişim tarihi
(dc.date.available)
2019-07-09T14:10:06Z
ISSN
(dc.identifier.issn)
1454-8658
Özet
(dc.description.abstract)
In 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.
Yayın Dili
(dc.language.iso)
en
Tek Biçim Adres
(dc.identifier.uri)
https://hdl.handle.net/20.500.12498/938
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