Genetic Neural Network for Diabetes Likelihood Prediction Using Risk Factors
Document Type
Conference Proceeding
Publication Date
2023
Abstract
Diabetes mellitus is a disease incorporated with carbohydrate metabolism whereas the body becomes unable to generate or react with insulin which leads to abnormal levels of blood sugar (glucose). In a worldwide perspective, Diabetes mellitus is ranked as the 9th leading cause of death based on the records of the World Health Organization and according to the International Diabetes Federation, there are about 463 million diabetic people worldwide in 2019 which is projected to increase to 700 million diabetic people by year 2045. In a regional perspective, about 251 million (45%) diabetic people resides on the Western Pacific and Southeast Asian region, whereas about 140 million people are undiagnosed of the disease. In this study, a genetic algorithm-optimized neural network using MATLAB was developed based on the risk factors. The experimental results show that the best validation performance has a value of 0.014129 and with a regression model coefficient R2 value of 0.95864.
Recommended Citation
R. P. C. Gamara, A. T. Teologo, K. H. A. Recto, R. Q. Neyra and A. A. Bandala, "Genetic Neural Network for Diabetes Likelihood Prediction Using Risk Factors," 2023 IEEE 15th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), Coron, Palawan, Philippines, 2023, pp. 1-5, doi: 10.1109/HNICEM60674.2023.10589131.
