Using case-based reasoning to diagnostic screening of children with developmental delay

According to the statistics of health organizations of the United Nations, population of children with developmental delay approximately takes 6-9% of the total population. Take the number of newborns (9420) in rural Yunlin County of Taiwan in year 2002 for estimation; there will be approximately 700 (cases regarded developmental delay with suspicion) suspect cases each year. When symptoms of these children are detected early and early intervention given appropriately, wastes in medical resources and social costs could be effectively reduced. Overseas researches show that for children with developmental delay, the best time to intervene is prior to the age of six, and it is golden treatment period before three and a half years old. Studies indicate that when developmentally delayed children receive early intervention, they will show significant improvement in symptoms; some might even recover completely. This study adopts the characteristics of case-based reasoning (CBR) to enhance the screening efficiency of children with developmental delay. CBR is a technology that resolves problems; it resolves currently encountered problems based on previous experiences, which is very similar to the way human beings solve problems by learning from experiences. Since CBR possesses memory functions, which allow it to make judgments and comparisons on new cases, based on old cases saved in the system previously, it is appropriate to apply CBR to a supporting system that has characteristics of invisibility and variation. Therefore, this study uses CBR to establish a screening system of developmental delayed children hoping to increase the screening efficiency. After system verification, the reasoning mean of case similarity is 0.92, and that of accuracy, 0.91, indicating a high level of verification results of this system, and thereby verifying a high level of feasibility of the system. (C) 2004 Elsevier Ltd. All rights reserved.