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- W1497474832 abstract "During the past 50 years, allergic diseases have increased in children in many countries with modern living conditions. Healthy lifestyle is easier to maintain when healthful patterns of behavior are learned early in life. For children, their parents make most of the decisions related to their health practices or behaviors. Additionally environment and socio-cultural factor contributes to the person’s ability to develop their optimum health. Therefore, it is important to understand what factors can influence the allergy symptoms in children. This study used data mining techniques as a tool to investigate the conditions that influence allergy symptoms, especially in respiratory area among children in Taiwan. Data mining is intelligent science of mining and extracting previously unidentified but potentially valuable information embedded in data. Data mining search valuable information by applying statistical, machine learning and pattern recognition. The goal of this study was to use such techniques to identify the main factors that cause allergy symptoms in children. The results of this study could be used as guidelines for developing strategies for allergy prevention." @default.
- W1497474832 created "2016-06-24" @default.
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- W1497474832 date "2008-01-01" @default.
- W1497474832 modified "2023-09-22" @default.
- W1497474832 title "DEPARTMENT OF COMPUTER SCIENCE AND INFORMATION ENGINEERING" @default.
- W1497474832 hasPublicationYear "2008" @default.
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