• Home
  • Browse
    • Current Issue
    • By Issue
    • By Author
    • By Subject
    • Author Index
    • Keyword Index
  • Journal Info
    • About Journal
    • Aims and Scope
    • Editorial Board
    • Publication Ethics
    • Indexing and Abstracting
    • Related Links
    • FAQ
    • Peer Review Process
    • News
  • Guide for Authors
  • Submit Manuscript
  • Reviewers
  • Contact Us
 
  • Login
  • Register
Home Articles List Article Information
  • Save Records
  • |
  • Printable Version
  • |
  • Recommend
  • |
  • How to cite Export to
    RIS EndNote BibTeX APA MLA Harvard Vancouver
  • |
  • Share Share
    CiteULike Mendeley Facebook Google LinkedIn Twitter
International Journal of Information, Security and Systems Management
arrow Articles in Press
arrow Current Issue
Journal Archive
Volume Volume 7 (2018)
Volume Volume 6 (2017)
Volume Volume 5 (2016)
Volume Volume 4 (2015)
Issue Issue 2
Issue Issue 1
Volume Volume 3 (2014)
Volume Volume 2 (2013)
Volume Volume 1 (2012)
Latifi, F., Hosseini, R., Mazinai, M. (2015). A Fuzzy Expert System for Diagnosis of Acute Lymphocytic Leukemia in Children. International Journal of Information, Security and Systems Management, 4(2), 424-429.
Farzaneh Latifi; Rahil Hosseini; Mahdi Mazinai. "A Fuzzy Expert System for Diagnosis of Acute Lymphocytic Leukemia in Children". International Journal of Information, Security and Systems Management, 4, 2, 2015, 424-429.
Latifi, F., Hosseini, R., Mazinai, M. (2015). 'A Fuzzy Expert System for Diagnosis of Acute Lymphocytic Leukemia in Children', International Journal of Information, Security and Systems Management, 4(2), pp. 424-429.
Latifi, F., Hosseini, R., Mazinai, M. A Fuzzy Expert System for Diagnosis of Acute Lymphocytic Leukemia in Children. International Journal of Information, Security and Systems Management, 2015; 4(2): 424-429.

A Fuzzy Expert System for Diagnosis of Acute Lymphocytic Leukemia in Children

Article 1, Volume 4, Issue 2, Autumn 2015, Page 424-429  XML PDF (693.41 K)
Document Type: Research Paper
Authors
Farzaneh Latifi1; Rahil Hosseini email 1; Mahdi Mazinai2
1Department of Artificial Intelligence, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
2Department of Electronic Engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
Abstract
Fuzzy expert systems are one of the most practical intelligent models with the high potential for managing uncertainty associated to the medical diagnosis. In this paper, a fuzzy inference system (FIS) for diagnosing of acute lymphocytic leukemia in children has been introduced. The fuzzy expert system applies Mamdani reasoning model that has high interpretability to explain system results to experts in a high level. The system has been designed based on the specialist physician’s knowledge. The proposed systems, has been implemented in Matlab and evaluated on real patients’ dataset. High accuracy of this system (with an accuracy about 96%) revealed its capability for helping experts to early diagnosis of the disease. that the results are promising for more earlier diagnosis and then providing good treatment of patients and consequently saving more children’s lives.
Keywords
fuzzy expert system; acute lymphocytic leukemia; diagnosing of leukemia
Statistics
Article View: 2,945
PDF Download: 3,694
Home | Glossary | News | Aims and Scope | Sitemap
Top Top

Journal Management System. Designed by sinaweb.