Fuzzy dynamic programming, fuzzy adaptive neuro control, and the general medical diagnosis problem

The fuzzy medical diagnosis decision models of Esogbue and Elder employed fuzzy sets theory to directly and more correctly model all the information nets useful in reaching a scientific understanding of a patient's health status. This knowledge was utilized in constructing a sensible medical hypothesis decision problem. In this paper, we show how fuzzy dynamic programming and neural networks can be used to extend the process to other phases by linking the four stages of medical hypothesis, physician's observation, preliminary diagnosis, and final diagnosis in an adroit manner.