A Novel flow for Reasoning of Medical Diagnostic System using Artificial Feed Forward Neural Networks

In its first part, this contribution reviews shortly the application of neural network methods to medical problems and characterizes its advantages and problems in the context of the medical background. Various research shows that diagnostic capabilities of human are worse than the neural network strategy to diagnose any pattern. Then paradigm of neural networks is introduced and the main problems of medical data base and the basic approaches for training and testing a network by medical data are described. Additionally, the problem of interfacing the network and its result is given and the optimal Back propagation algorithm approach is presented. Finally, as case study of neural rule based diagnosis septic shock diagnosis is described, on one hand by a growing neural network and on the other hand by a rule based system.