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:: Volume 20, Issue 1 ( Winter 2017, 20 (1) 2018) ::
koomesh 2018, 20(1): 71-80 Back to browse issues page
Comparison of multilayer perceptron neural network based on wrapper algorithm, discriminant analysis and logistic regression in determining risk factors of type 2 diabetes
Eghbal Zandkarimi , Majid Sadeghifar * , Mansour Rezaei
Abstract:   (1190 Views)
Introduction: The present study aimed to evaluate the performance of three statistical models in predicting diabetes type 2 as well as to identify its risk factors.
Materials and Methods: The data related to the potential risk factors of body mass index (BMI), fasting blood sugar (FBS), hypertension (HT), lipids (TC, TG, HDL and LDL), HbA1C and smoking history of 300 patients were extracted from medical records. Artificial neural network multi-layer perceptron (MLP), discriminant analysis (DA) and logistic regression (LR) were applied to identify risk factors. ROC curve was used to compare the performance of the models. To fix the problem "over fitting", the MLP model algorithm was used Wrapper.
Results: The prediction power of the MLP, DA and LR based on the ROC curve were 0.984, 0.981and 0.983, respectively. In the LR model, variables FBS (P<0.0001) and HbA1C (P<0.0001), weight (P<0.001), BMI (P<0.01) and LDL (P<0.003) were significant. In the DA model, variables HT, Smoking status, Hba1c, FBS (all, P<0.0001) were significant. Age, FBS, TG, HbA1C, BMI, HT and TC were significant in the MLP model. The MLP showed higher sensitivity (97%) compared with the LR (94%) and the DA (92%). Also, the model MLP (97%) exhibited high specificity than the LR (92%) and DA (93.3%).
Conclusion: According to the findings of the present study, the performance of the three used methods of MLP, LR and DA were similar. It is suggested to use the LR where there is a need to simple interpretation as it provides OR for a group relative to the other one while MLP acts like a black box that does not show the relationship between variables. It is also suggested to conduct studies for further investigation of the performance of these methods.
Keywords: Artificial Neural Network MLP, Logistic Regression, Discriminant Analysis, Wrapper, Curve Rock
Full-Text [PDF 761 kb]   (162 Downloads)    
Type of Study: Research | Subject: General
Received: 2016/10/4 | Accepted: 2017/04/8 | Published: 2018/01/1
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zandkarimi E, Sadeghifar M, Rezaei M. Comparison of multilayer perceptron neural network based on wrapper algorithm, discriminant analysis and logistic regression in determining risk factors of type 2 diabetes. koomesh. 2018; 20 (1) :71-80
URL: http://koomeshjournal.semums.ac.ir/article-1-3648-en.html


Volume 20, Issue 1 ( Winter 2017, 20 (1) 2018) Back to browse issues page
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