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

Authors:
Novruz Allahverdi;Ayfer Tunali;Hakan IşIk;Humar Kahramanli
Affiliations:
Electronic and Computer Education Department, Selcuk University, Konya, Turkey;Health Services Vocational High School, Kocaeli University, Izmit, Turkey;Electronic and Computer Education Department, Selcuk University, Konya, Turkey;Electronic and Computer Education Department, Selcuk University, Konya, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

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.