A hybrid fuzzy neural network analysis to the risk factors of type 2 diabetes
| Autor: | Te-Jen Su, Shih-Ming Wang, Feng-Chun Lee, Tzung-Shiarn Pan |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | International Journal of Modern Physics B. 35:2140035 |
| ISSN: | 1793-6578 0217-9792 |
| DOI: | 10.1142/s021797922140035x |
| Popis: | The number of people suffering from diabetes in Taiwan has been increasing in recent years, according to data from the Health Promotion Administration, the prevalence rate of diabetes in Taiwan has reached 5%. In 2019, there were approximately 1.1 million type 1 diabetes patients under the age of 20 in the world, indicating that diabetes is also threatening the health of children and adolescents. Moreover, the vast majority of about 463 million diabetic patients globally between the ages of 20 and 79 suffer from type 2 diabetes. One can see that diabetes is an important public health problem and one of the four major noncommunicable diseases that leaders of all countries should take priority action to address. Type 2 diabetes causes many complications, including cardiovascular disease, impaired vision, amputation, kidney disease, etc. and increases the cost of social medical care. This study takes data from the Data Database of the Health Promotion Administration as the parent population, fuzzy theory and neural network to build predictive models with Matlab tools. The predictive results can be used as a reference for medical personnel in any diagnosis. |
| Databáze: | OpenAIRE |
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