مطالعه با استفاده از داده کاوی برای مداخله به موقع برای رشد تاخیر افتاده کودکان
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|22100||2014||6 صفحه PDF||سفارش دهید||3700 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 33, Issue 2, August 2007, Pages 407–412
The implementation of early intervention has close relation to the growth development of developmentally-delayed children. The earlier the intervention is involved the more significant effects and results it will bring to the benefits of these young children. However, providing early intervention exclusively without finding out the relationship between the two would eventually leave the problematic point remain unsolved. Since a child’s becoming developmental delay is resulted from many factors, much of the valuable knowledge among all needs to be unveiled. In the process of knowledge discovery, use data mining approach to nugget out potential knowledge from vast amounts of data. The main purpose of this study is to explore the hidden knowledge among medical history data of developmentally-delayed children. Fields of medical history database belongs to set and binary, so decision tree is constructed to classify delay levels of each type according to physical illness, and association rule is applied to locate correlations between cognitive, language, motor, and social emotional developmental delays. The study results indicate that the majority of illnesses will result in delays in cognitive, language, and motor development. Simultaneously, among all types of delay, motor and cognitive delay mostly accompanies with symptoms of language delay. The results of this study enable healthcare professionals to be on top of the developments of young children during the process of evaluation and diagnosis, and to provide early intervention so that developmentally-delayed children can catch up with their normal peers in development and growth.
In recent years, the average number of infants given birth by fertile women between the ages of 15 and 49 years olds has slid down from 1.68 in year 2000 to 1.24 now. Reasons for that are worth discussing. At much earlier era when medical care technology was not fully mature and intervention service mechanism not fully developed, parents, for financial reasons and sometimes being afraid of losing faces, often were unable to appropriately help raising young children who are mentally or physically disabled. As a result, these children missed out on the golden timing of receiving assistances and rehabilitations. Since this is a serious problem that affects national population growth ratio, many related children welfare laws have been legislated by the government. For instance, articles in “Children Welfare Law” promulgated in 1993 establishes related policies focusing on mentally and physically disabled children specially as stipulated in paragraph 2 of article 13, “all children and youth welfare, education and medical institutions at all levels shall communicate with the municipal and county (city) government authorities if finding any children and youth with allegedly retarded development, or physical or mental disability. The municipal and county (city) government authorities shall establish the databank for management upon receipt of the information, and transfer to appropriate services if necessary”. Then in April 1997, the “protection law for mentally and physically disabled” was promulgated, with its emphasis on “protection” and “rehabilitation” that actively intervenes and prevents the occurrence of mentally and physically disabled population. “Children’s Bureau Ministry of Interior ROC” is established in November 1999, an institution responsible for managing and processing nationwide children welfare business. To truly protect the interests and rights of children and youth, the “Children and Youth Welfare Law” is passed in May 1993, and explicitly stipulated in the 1st paragraph of article 19 “to establish the early communication system for children with retarded development and provide early treatment”. Although the need and importance for early intervention was brought up early when the government actively enacted related rules and regulations, no in-depth analysis for causes of developmental delay children and relationships of delays has been discussed yet. According to the January “Technology Review” in 2000 at Massachusetts Institute of Technology (MIT), it is predicted that data mining is among the top 10 new emerging technologies that would change the future world. As a result, data mining is the most commonly used technology with applications widely ranging in different fields, including banking, finance, marketing, manufacturing, healthcare, and etc. Moreover, studies that use case-based reasoning to early interventions have proved to have excellent effects (Chang, 2005), whereas applying data mining technique to areas of retarded development is rarely seen. This study, through medical history of developmentally-delayed young children, uses decision tree to classify and predict which illness will bring out which type of delay from causes of illness classification, vision problems, psycho-intellectual aspects, other physical diseases, etc. Also, it uses association rule to determine correlations among cognitive, language, motor, and social emotional development delays to nugget useable knowledge hidden behind the vast database so that medical care personnel can utilize such valuable knowledge to provide young children with appropriate treatments during examinations.
نتیجه گیری انگلیسی
Children are the hope of the future and the foundation of economics for national development. Western countries like the United States and in Europe have implemented child-related laws and regulations for years in hope of children growing up healthily. In the recent decade, child-related laws and regulations in Taiwan have drawn much attention of the public. This study conducts data mining focusing specifically on developmentally-delayed children, applies data mining approach to find the hidden knowledge in the huge database, and, through data mining analysis, obtains useful information for use of healthcare personnel as a reference in decision making and evaluation. This study has identified which type of illness items will cause certain types of delays by building a decision tree; moreover, it utilizes association rule analysis to determine the correlations among cognitive, language, motor, social emotional developmental delays. The results of this study can provide healthcare personnel important references during diagnosis and evaluations to keep track on the growth conditions of young children so that early treatment is possible for those who are developmentally-delayed and that they can catch up with other normal children in growth and development.