Fuzzy Rule-Based Expert System for Assessment Severity of Asthma

  • Authors:
  • Maryam Zolnoori;Mohammad Hossein Zarandi;Mostafa Moin;Shahram Teimorian

  • Affiliations:
  • Department of Information Technology Management, Tarbiat Modares University, Tehran, Iran and Mathematic and informatics group, Academic Center for Education, Culture and Research (ACECR), Tarbiat ...;Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran;Immunology, Asthma and Allergy Research Institute, Tehran University of Medical Sciences, Tehran, Iran;Immunology, Asthma and Allergy Research Institute, Tehran University of Medical Sciences, Tehran, Iran

  • Venue:
  • Journal of Medical Systems
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

Prescription medicine for asthma at primary stages is based on asthma severity level. Despite major progress in discovering various variables affecting asthma severity levels, disregarding some of these variables by physicians, variables' inherent uncertainty, and assigning patients to limited categories of decision making are the major causes of underestimating asthma severity, and as a result low quality of life in asthmatic patients. In this paper, we provide a solution of intelligence fuzzy system for this problem. Inputs of this system are organized in five modules of respiratory symptoms, bronchial obstruction, asthma instability, quality of life, and asthma severity. Output of this system is degree of asthma severity in score (0---10). Evaluating performance of this system by 28 asthmatic patients reinforces that the system's results not only correspond with evaluations of physicians, but represent the slight differences of asthmatic patients placed in specific category introduced by guidelines.