Disease Prediction and Diagnosis implementing Fuzzy Neural Classifier Based on IoT and Cloud

  • Eka Erwansyah, Barunawaty Yunus, Irene E. Rieuwpassa, Fuad Husain Akbar, Tami Suryawansa

Abstract

Skeletal maturation is multifactorial. The aim of this study is to analyse the relationship between body mass index and skeletal maturation in children aged 8-15 years old. Thirty one cephalometric lateral radiograph (20 females and 11 males) were registered as orthodontic patients and calculated by Lamparski method. Body mass index calculated by age-based BMI formula, then grouped according to the classification established by the Center of Disease Control and Prevention (CDC). The relationship between body mass index and skeletal maturation was analyzed through the Chi-square correlation test. The results of statistical tests (p<0.05) showed a significant correlation between the BMI value and skeletal maturation based on chronological age. There is a relationship between the Body Mass Index and skeletal maturation in children. The greater the BMI value, skeletal maturation will be faster. Conversely, the smaller the BMI value,  the Skeletal maturation will be slower.

Published
2020-04-15
How to Cite
Eka Erwansyah, Barunawaty Yunus, Irene E. Rieuwpassa, Fuad Husain Akbar, Tami Suryawansa. (2020). Disease Prediction and Diagnosis implementing Fuzzy Neural Classifier Based on IoT and Cloud. International Journal of Advanced Science and Technology, 29(05), 737 - 745. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/9605