Diagnose Of The Respiratory Diseases By Using Fuzzy Logic

In recent years, the methods of Artificial Intelligence have largely been used in the different areas including the medical applications. In the medicine area, many expert systems (ESs) were designed, being the backbone of diagnosing the respiratory diseases, needs to be focused and new techniques for all diseases in human's body are required to be developed relating to it.In our work used expert systems, so we design an expert system to diseases diagnosis by using Fuzzy set depending on doctor's opinions.approach that used is fuzzy set to diseases diagnosis depending on opinion of 20 doctors, and the out puts it have been to diagnose three types of respiratory diseases (primary kinds of respiratory diseases) (pneumonia (PEN), tuberculosis (TB) and normal influenza (INF)), there are four symptoms it will inter into computer as numerical data inputs, X- ray, Respiratory rate (RR), Cough (CO) and Fever (F) which indicate as input of the fuzzy logic and the outputs will be a range of the risks and one type of three respiratory diseases.In this work we will discussed how to diagnosis of the diseases by using an Artificial intelligent (Fuzzy set) exploration of alternative approaches for traditional diagnosis, however it is more important to consider the Problem-solving process.This thesis studies the problem of medical diagnosis basically from the second point of view, although recognizes the necessity of paying attention to some of the details in any complex problem domain.It attempts to fit the problem of medical diagnosis into the formwork of the fuzzy set and paradigms and in particular explores the notions of pure.The research implemented for three stage,the first stage a doctor will check paints then taking his or her symptoms as temperature and so on.Second stage it will be inter numerical data to that program, last stage we implement that program to obtain on the result,all those stages...