شنبه 1 دی 1403
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دوره 30، شماره 140 - ( 2-1401 )
جلد 30 شماره 140 صفحات 288-281 |
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Jahanbakhsh M, Aghadavodian Jolfaee A, Kelishadi R, Sattari M. Extracting the Hidden Patterns Affecting Mental Health through Data Mining Techniques. J Adv Med Biomed Res 2022; 30 (140) :281-288
URL: http://journal.zums.ac.ir/article-1-6319-fa.html
URL: http://journal.zums.ac.ir/article-1-6319-fa.html
Extracting the Hidden Patterns Affecting Mental Health through Data Mining Techniques. Journal of Advances in Medical and Biomedical Research. 1401; 30 (140) :281-288
چکیده: (83195 مشاهده)
Background and Objective: This study was conducted to shed light on the hidden relationships, trends, and patterns of the teenagers’ mental health dataset based on data mining techniques.
Materials and Methods: The proposed method has four parts as follows: data preprocessing, data cleaning, target class selection, and extracting rules. The classes included inappropriate, moderate, and acceptable. The rules were extracted separately by implementing ID3, CHAID, and rule induction on the Caspian 5 dataset.
Results: It was found that the teenagers who rarely drink carbonated soda and have dinner seven days a week, have acceptable status of mental health. Besides, watching TV and playing computer games for 4 hours or more per week, drinking tea and packaged juices, eating cakes, cookies, pastries, biscuits, and chocolate weekly could lead to inappropriate status of mental health.
Conclusion: An attempt to improve health especially in youth is one of the important concerns of every country. The rules express the negative impact of soda on mental health. Besides, it can be concluded that there is a direct relationship between having breakfast and mental health.
نوع مطالعه: مقاله پژوهشی |
موضوع مقاله:
Epidemiologic studies
دریافت: 1399/9/15 | پذیرش: 1400/2/28 | انتشار: 1401/1/12
دریافت: 1399/9/15 | پذیرش: 1400/2/28 | انتشار: 1401/1/12
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