A Takagi-Sugeno type neuro-fuzzy network for determining child anemia

作者：Allahverdi Novruz; Tunali Ayfer; Isik Hakan; Kahramanli Humar^*

来源：Expert Systems with Applications, 2011, 38(6): 7415-7418.

DOI：10.1016/j.eswa.2010.12.083

• TSK-type neuro-fuzzy networks
• Anemia

Decision-making is a difficult and quite responsible task for doctors. Some of the computer decision models assisted the doctor with some computer decision models. In this study, neuro-fuzzy network has been designed to determine anemia level of a child. The performance analyses have been obtained by leaving-one-out cross-validation. After statistical measurements, it was found that MPE = 0.0018, MAE = 0.2090, MAPE = 0.0511, RMSE = 0.2743 and R(2) = 0.9957 of this developed system. According to these results, the designed neuro-fuzzy network may be considered as adequate close to traditional decision-making methods and thus the designed network can be used effectively for child anemia prediction.

• 出版日期2011-6