Classification of Iraqi Children According to Nutritional Status Using Fuzzy Decision Tree

Abstract

The classification is one of the essential tools used in medical statistics to classify the nutritional status of children under five years. A good nutritional status is necessary for children's health and has a sicnificant role in the child's normal development. Likewise, poor nutritional status is considered a serious disease for this age group and needs attention from child health specialists. Doctors face great difficulty in determining the nutritional status due to the state of uncertainty in the incidence of this disease or the ambiguity in the variables and characteristics of that phenomenon. The fuzzy sets theory was applied to classify the nutritional status of children under the age of five years using fuzzy logic, where the fuzzy decision tree method was employed, and a tree was created for each age group (male, female) based on the linguistic variables (weight, height), and body mass index for the classification categories. In this study, the nutritional status of children was classified and the groups were identified more accurately to reduce the chances of misdiagnosis and provide them with more accurate appropriate treatment to improve the health level of children to build a more immune society with a good health level.

    The study dealt with a sample of (16487) Iraqi children under 5 years of age, the number of males (8427) and the number of females (8060), divided according to age into 12 categories or groups. The results showed the age groups She was of normal weight in varying proportions.