Prediction of Gestational Diabetes Using Discriminant Analysis Algorithm

The IJNCPS's Authors that presented the article:

  • amin golabpour Shahroud University of Medical Sciences, Shahroud, Iran
Keywords: Gestational diabetes, data mining, discriminant analysis, prediction


Gestational diabetes is a condition in which increases in blood sugar level is seen for the first time during pregnancy. Gestational diabetes occurs in about four percent of pregnancies. The exact cause of gestational diabetes is ambigous, but the presence of some cues is effective in early diagnosis of the disease. Diabetes prevention and control during pregnancy is essential from point of view the complications of diabetes for the fetus and the pregnant mother. In this study, eight data mining algorithms are compared and it is found that the discriminant analysis algorithm performs better than other algorithms and reaches an accuracy of 78.02%.


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