Artificial Intelligence and Neural Networks With Rules-Based Filter Are Useful to Find Correlations Between Diet and the Health Status of Multiple Sclerosis Patients
In this article we address three different problems of “Surface Analysis” thanks to Artificial Intelligence with Neural Networks related to the diet of the person newly affected by multiple sclerosis, a diet that can be myelinating or demyelinating; the second has the objective of recognizing whether oil, or water, can be present in a site and the presumed depth; the third objective is to classify radioactive atoms, such as Plutonium, on a neutral surface, as a sort of “Identity Card”. The data were collected, not on sites or authors that deal with the topic in question, but thanks to what emerges in summary form in the most common browsers, called in this work “data found on the volatile web”. It should be noted that the following chapters of this article do not aim to be precise and complete, but only to provide some ideas presented in a preliminary form to be explored in further studies. Each reader can draw the various indications, interpreting, thanks to the preliminary results, to modify the various “Intelligent” systems and proposing modifications to the various proposed architectures; This aspect must be considered carefully and recursively in all three chapters that follow. In a second stage, the bibliographical sources will also have to be studied in depth, finding help also from the various authors to be taken into consideration. remembering that the various problems, present in the three chapters, have been addressed by transforming them into a “surface” analysis
