JOURNAL OF COMPUTING, VOLUME 2, ISSUE 6, JUNE 2010, ISSN 2151-9617 HTTPS://SITES.GOOGLE.COM/SITE/JOURNALOFCOMPUTING/ WWW.JOURNALOFCOMPUTING.ORG 67 decision support tools and a standard framework for the exchange of health information, over inexpensive Internet communication pathways using web-based technologies.Informantion related to this can be found from the website of National Research Council Canada [5]. 

 YourDiagnosis [6] is developed by an expert panel of very experienced doctors in Australia. They are part of a large medical and hospital group called Macquarie Health Corporation Ltd. Macquarie Health Corporation Ltd. also owns Macquarie Hospital Services and Macquarie Medical Systems. Macquarie Hospital Services has owned and operated private hospitals since 1976. 

 Easy Diagnosis [7] is a online diagnosis system. This expert system software provides a list and clinical description of the most likely conditions based on an analysis of patient's particular symptoms. EasyDiagnosis focuses on the most common medical complaints that account for the majority of physician visits and hospitalizations. 

 Wrong Diagnosis [8] which is part of Health Grades network and WebMD [9] whose slogan is "Better Information, Better Health" are another two efficient online diagnosis tools. 

 There are many online diagnosis tool in the web, but proposed system is the most user friendly (easy to use), 
precise, at the same time accurate. In the web, some systems are so boring -needs to give lots of information, give answers to lots of question which is quite monotonous. In most of the other online diagnosis websites, the sequence of questions is fixed. 

 But in the proposed system one needs to give minimal information, questions will be asked after filtering at every step based on your responses and at every step the problem domain will become narrower to reach a perfect diagnosis. 

## 3 Proposed Fuzzy Expert System For Human Disease Diagnosis

Different diagnosis strategies have been studied. Different e-health websites have been browsed. Papers and articles on e-health management have been read and different diagnosis tools have been used. Noted down important information like which information they are collecting from the user/ patients and which approach they are following in diagnosis. 

Then information (symptom, signs etc.) of different diseases have been collected for particular category as sample [8, 9, 10]. Made a comparative analysis to identify which symptoms are major symptoms for particular diseases i.e. that symptom must be present, their acuity level etc. 

Then met with few doctors with different level of expertise in their field. Asked them about those diseases and their symptoms, which factors they consider while they diagnosis diseases, what approach they follow. 

After studying and making a comparative analysis of what is gotten by consulting with different doctors about which factors they consider while they diagnosis diseases, what approach they follow, it is found that they are almost same. Then a uniform structure is made and a mathematical equivalence (equation (3.1)) is formed, which will be used to diagnosis by the fuzzy expert system. 

After that implementation of the expert system is done and tested it thoroughly to check whether the desired result is coming or not. After necessary corrections, when it seems ok with respect to the desired goal, then consulted with the doctors again and explained about the software implementation and showed it to them and they acknowledged it, gave some suggestions(to add catalyst factor which is some sort of personal information/ patient's history information), according to which the system is revised. 

Probability of diseases is measured using equation (3.1) 
whose value depends on the user feedback while diagnosing. 

Probability disease =  ($\Sigma$S${}_{\rm i}$*W${}_{\rm i}$ - $\Sigma$(S${}_{\rm major}$)${}_{\rm j}$(W${}_{\rm max}$)${}_{\rm i}$) - Min${}_{\rm th}$  Max${}_{\rm th}$ - Min${}_{\rm th}$  (3.1)
wherei,j= counter of different symptoms Si = is ith symptom selected or not Wi = weight of ith symptom 
(Smajor)j = jth major symptom which is not selected by the user 
(Wmajor)j = weight of jth major symptom Maxth = maximum threshold of disease Minth = minimum threshold of disease 
∑SiWi = total weight of a disease based on the selected symptom 
∑(Smajor)j(Wmajor)j = total weight of unselected major symptoms of a disease Cf = catalyst factor based on patient's history/personal information The proposed expert system assist user to diagnosis diseases, he/she might have, in a fuzzy way. Based on the selection of the problem area/problem, the expert system gives some symptom from which the user needs to select symptoms, based on the selection of symptoms the user is asked some questions, according to the answer selection the fuzzy expert system diagnosis diseases based on it's knowledge, add catalyst factor (if any) and do ranking and gives result in fuzzy form. 

Fig. 1. represents the flow diagram of the proposed system. 