1. A neural network system, comprising: i) an input layer configured to accept N input signals; ii) one or more “i” hidden layers, iii) at least one output layer; iv) at least one neuron “Y layer ” within each layer, where “layer” is the layer defined as “input”, “hidden i ” or “output”; and, v) one or more memory structures configured to: a) store a recursive memory of input signals past, and b) allow for at least one time series prediction of a response, wherein the neural network is configured to include one or more input variables oriented trend analysis post processing algorithms which are configured to analyze one or more predicted outputs of the neural network system for one or more expected trends in predicted analyte values based on previous and current input data presented to the neural network system; wherein one or more support/post processing algorithms are included in order to modify the neural network system predictive output such that an increased predictive accuracy is achieved; and wherein the neural network includes a support/post processing algorithm comprising an input variable, or event, oriented trend analysis algorithm.