Using Decision Tree and Response Surface Methodology to Review Chronic Periodontitis Profile in Pakistan: a Preliminary Case Study

 
 
 
  • Abstract
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  • Abstract


    Chronic periodontitis is among the most prevalent oral diseases in the world. Apart from its destructive outcomes in the oral cavity, there is a strong evidence of the potential association between chronic periodontitis and systemic diseases such as cardiovascular disease, diabetes, and preterm low birth weight. In this paper, the potential contributing factors which lead to chronic periodontitis will be      determined among the patients attending Islamabad Dental Hospital by response surface methodology (RSM) and decision tree (DT) analysis. The results of this study show that the prevalence of severe chronic periodontitis is high in patients who have not brushed their teeth (23.5%) and for the case without the severity of chronic periodontitis (61.1%). Whereas, from the RSM analysis, it is shown that there is an association between chronic periodontitis, diabetic status, and frequency of smoking. However, using DT analysis, age and frequency of brushing were the best predictors of severe chronic periodontitis. This present study concludes that by using RSM and DT analysis can predict a better forecasting result in future for the decision making among the decision maker.

     

     


  • Keywords


    Chronic Periodontitis; Response Surface Methodology; Decision Tree.

  • References


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Article ID: 20971
 
DOI: 10.14419/ijet.v7i3.28.20971




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