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Information Journal Paper

Title

Comparing of Decision Tree with Logistic Regression Model in Evaluating Osteoporosis

Pages

  14-23

Abstract

 Introduction: Early detection of Osteoporosis is a key to preventing of it; but recognition, without the use of appropriate diagnostic methods, due to the complexity of risk factors and gradual bone loss process, is problem. The purpose of this study is to develop and efficiency evaluation a predictive model of Osteoporosis using Decision Tree technique as a diagnostic method based on available risk factors; thereby to identify individuals at risk for preventive activities. Methods: In this study used data from 131 women aged 20 – 40 years. Response variable was amount of BMD (t-score) L1-L4 lumbar region that divided on two group, normal (t-score>=-1) and at risk of Osteoporosis (t-score<-1). To determine risk factors of Osteoporosis used from Decision Tree model with method of k-fold cross validation k=4 and logistic regression. To assess the accuracy prediction of two model, the Area under receiver operative characteristic curves (AUROC) was used. Data analysis was performed by R software. Results: Three variables number of pregnancies, BMI and calcium levels as risk factors for Osteoporosis were obtained from the Decision Tree model and Area under receiver operative characteristic Decision Tree and logistic regression, respectively 0. 665 and 0. 686 were obtained. Conclusion: Area under receiver operative characteristic curve showed advantage superiority of logistic regression that according to advantages of the Decision Tree applying simultaneously of two models is recommended.

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    APA: Copy

    ASKARISHAHI, MOHSEN, Ghasemi, Nasime, Flahzadeh, Hossein, AFKHAMI ARDEKANI, MOHAMMAD, & AFKHAMI ARDEKANI, AREZOO. (2018). Comparing of Decision Tree with Logistic Regression Model in Evaluating Osteoporosis. TOLOO-E-BEHDASHT, 17(1 (67) ), 14-23. SID. https://sid.ir/paper/102851/en

    Vancouver: Copy

    ASKARISHAHI MOHSEN, Ghasemi Nasime, Flahzadeh Hossein, AFKHAMI ARDEKANI MOHAMMAD, AFKHAMI ARDEKANI AREZOO. Comparing of Decision Tree with Logistic Regression Model in Evaluating Osteoporosis. TOLOO-E-BEHDASHT[Internet]. 2018;17(1 (67) ):14-23. Available from: https://sid.ir/paper/102851/en

    IEEE: Copy

    MOHSEN ASKARISHAHI, Nasime Ghasemi, Hossein Flahzadeh, MOHAMMAD AFKHAMI ARDEKANI, and AREZOO AFKHAMI ARDEKANI, “Comparing of Decision Tree with Logistic Regression Model in Evaluating Osteoporosis,” TOLOO-E-BEHDASHT, vol. 17, no. 1 (67) , pp. 14–23, 2018, [Online]. Available: https://sid.ir/paper/102851/en

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