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Information Journal Paper

Title

A Comparison between Decision Tree and Random Forest in Determining the Risk Factors Associated with Type 2 Diabetes

Pages

  1-7

Abstract

 Background: We aimed to identify the associated risk factors of type 2 Diabetes mellitus (T2DM) using data mining approach, Decision tree and Random forest techniques using the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) Study program. Study design: A cross-sectional study. Methods: The MASHAD study started in 2010 and will continue until 2020. Two data mining tools, namely Decision trees, and Random forests, are used for predicting T2DM when some other characteristics are observed on 9528 subjects recruited from MASHAD database. This paper makes a comparison between these two models in terms of accuracy, sensitivity, specificity and the area under ROC curve. Results: The prevalence rate of T2DM was 14% among these subjects. The Decision tree model has 64. 9% accuracy, 64. 5% sensitivity, 66. 8% specificity, and area under the ROC curve measuring 68. 6%, while the Random forest model has 71. 1% accuracy, 71. 3% sensitivity, 69. 9% specificity, and area under the ROC curve measuring 77. 3% respectively. Conclusions: The Random forest model, when used with demographic, clinical, and anthropometric and biochemical measurements, can provide a simple tool to identify associated risk factors for type 2 diabetes. Such identification can substantially use for managing the health policy to reduce the number of subjects with T2DM.

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    APA: Copy

    ESMAILY, HABIBOLLAH, TAYEFI, MARYAM, DOOSTI, HASSAN, GHAYOUR MOBARHAN, MAJID, Nezami, Hossein, & Amirabadizadeh, Alireza. (2018). A Comparison between Decision Tree and Random Forest in Determining the Risk Factors Associated with Type 2 Diabetes. JOURNAL OF RESEARCH IN HEALTH SCIENCES (JRHS), 18(2), 1-7. SID. https://sid.ir/paper/301593/en

    Vancouver: Copy

    ESMAILY HABIBOLLAH, TAYEFI MARYAM, DOOSTI HASSAN, GHAYOUR MOBARHAN MAJID, Nezami Hossein, Amirabadizadeh Alireza. A Comparison between Decision Tree and Random Forest in Determining the Risk Factors Associated with Type 2 Diabetes. JOURNAL OF RESEARCH IN HEALTH SCIENCES (JRHS)[Internet]. 2018;18(2):1-7. Available from: https://sid.ir/paper/301593/en

    IEEE: Copy

    HABIBOLLAH ESMAILY, MARYAM TAYEFI, HASSAN DOOSTI, MAJID GHAYOUR MOBARHAN, Hossein Nezami, and Alireza Amirabadizadeh, “A Comparison between Decision Tree and Random Forest in Determining the Risk Factors Associated with Type 2 Diabetes,” JOURNAL OF RESEARCH IN HEALTH SCIENCES (JRHS), vol. 18, no. 2, pp. 1–7, 2018, [Online]. Available: https://sid.ir/paper/301593/en

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