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


ALLAHVERDİ N., Tunali A., IŞIK H., KAHRAMANLI H.

EXPERT SYSTEMS WITH APPLICATIONS, vol.38, pp.7415-7418, 2011 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 38 Issue: 6
  • Publication Date: 2011
  • Doi Number: 10.1016/j.eswa.2010.12.083
  • Title of Journal : EXPERT SYSTEMS WITH APPLICATIONS
  • Page Numbers: pp.7415-7418

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. (c) 2010 Elsevier Ltd. All rights reserved.