title: A novel AIDS/HIV intelligent medical consulting system based on expert systems.
abstract: BACKGROUND
  The purpose of this paper is to propose a novel intelligent model for AIDS/HIV data based on expert system and using it for developing an intelligent medical consulting system for AIDS/HIV.
  
  
  METHODS
  In this descriptive research, 752 frequently asked questions (FAQs) about AIDS/HIV are gathered from numerous websites about this disease. To perform the data mining and extracting the intelligent model, the 6 stages of Crisp method has been completed for FAQs. The 6 stages include: Business understanding, data understanding, data preparation, modelling, evaluation and deployment. C5.0 Tree classification algorithm is used for modelling. Also, rational unified process (RUP) is used to develop the web-based medical consulting software. Stages of RUP are as follows: Inception, elaboration, construction and transition. The intelligent developed model has been used in the infrastructure of the software and based on client's inquiry and keywords related FAQs are displayed to the client, according to the rank. FAQs' ranks are gradually determined considering clients reading it. Based on displayed FAQs, test and entertainment links are also displayed.
  
  
  RESULTS
  The accuracy of the AIDS/HIV intelligent web-based medical consulting system is estimated to be 78.76%.
  
  
  CONCLUSIONS
  AIDS/HIV medical consulting systems have been developed using intelligent infrastructure. Being equipped with an intelligent model, providing consulting services on systematic textual data and providing side services based on client's activities causes the implemented system to be unique. The research has been approved by Iranian Ministry of Health and Medical Education for being practical.
authors.affiliation: Department of Information Technology Management, Islamic Azad University, Electronic Campus, Tehran, Iran.
authors.forename: Alireza Pour
authors.initials: AP
authors.lastname: Ebrahimi
authors.forename: Abbas
authors.initials: A
authors.lastname: Toloui Ashlaghi
authors.forename: Maryam
authors.initials: M
authors.lastname: Mahdavy Rad
keywords: AIDS/HIV; data mining; intelligent system; medical informatics; software engineering; text mining