Artificial Intelligence and Neural Networks With Rules-Based Filter Are Useful to Find Correlations Between Diet and the Health Status of Multiple Sclerosis Patients

Abstract

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