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Extracting the Hidden Patterns Affecting Mental Health Through Data Mining Techniques Publisher



Jahanbakhsh M1 ; Jolfaee AA2 ; Kelishadi R3 ; Sattari M1
Authors
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Authors Affiliations
  1. 1. Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
  2. 2. Dept. of Management and Health Information Technology, Isfahan University of Medical Sciences, Isfahan, Iran
  3. 3. Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Journal of Advances in Medical and Biomedical Research Published:2022


Abstract

Background & 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 & 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. © 2022, Zanjan University of Medical Sciences and Health Services. All rights reserved.
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