Determination of Women Iron Deficiency Anemia Using Neural Networks

Abstract

Iron deficiency anemia (IDA) is a common type of anemia which most often occurs in young adult women. Detection of Iron deficiency requires blood tests and doctors' decision. Doing so can be costly and difficult especially in undeveloped countries. In this study, we developed an application by using Feedforward Networks (FFN), Cascade Forward Networks (CFN), Distributed Delay Networks (DDN), Time Delay Networks (TDN), Probabilistic Neural Network (PNN), and Learning Vector Quantization (LVQ) networks that can diagnose iron deficiency anemia in women.