Data Mining Approach for the Early Risk Assessment of Gestational Diabetes Mellitus
| Autor: | Saeed Rouhani, Maryam Mirsharif |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Pediatrics
medicine.medical_specialty 030219 obstetrics & reproductive medicine business.industry 02 engineering and technology medicine.disease Gestational diabetes 03 medical and health sciences 0302 clinical medicine 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing business Risk assessment |
| Zdroj: | International Journal of Knowledge Discovery in Bioinformatics. 8:1-11 |
| ISSN: | 1947-9123 1947-9115 |
| DOI: | 10.4018/ijkdb.2018010101 |
| Popis: | In this article, the authors proposed the method of medical diagnosis in gestational diabetes mellitus (GDM) in the initial stages of pregnancy to facilitate diagnoses and prevent the affection. Nowadays, in industrial modern world with changing lifestyle alimental manner the incidence of complex disease has been increasingly grown. GDM is a chronic disease and one of the major health problems that is often diagnosed in middle or late period of pregnancy, when it is too late for prediction. If it is not treated, it will make serious complications and various side effects for mother and child. This article is designed for answering to the question of: “What is the best approach in timely and accurate prediction of GDM?” Thus, the artificial neural network and decision tree are proposed to reduce the amount of error and the level of accuracy in anticipating and improving the precision of prediction. The results illustrate that intelligent diagnosis systems can improve the quality of healthcare, timely prediction, prevention, and knowledge discovery in bioinformatics. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|