Computer-Aided Intelligent System for Diagnosing Pediatric Asthma

  • Authors:

  • Maryam Zolnoori;Mohammad Hossein Fazel Zarandi;Mostafa Moin;Hassan Heidarnezhad;Anoshirvan Kazemnejad

  • Affiliations:

  • Mathematic and informatics group, Academic Center for Education, Culture and Research (ACECR), Tarbiat Modares University, Tehran, Iran;Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran;Immunology, Asthma and Allergy Research Institute, Tehran University of Medical Sciences, Tehran, Iran;Masih Daneshvari Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran;Department of Biostatistics, School of Medical Sciences, Tarbiat Modares University, Tehran, Iran

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

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Abstract

Asthma is a lung chronic inflammatory disorder estimated between 1.4% and 27.1% in different area of the world. Result of various studies show that asthma is usually underdiagnosed especially in developing countries, because of limitations on access to medical specialists and laboratory facilities. In this paper, we report on the development and evaluation of a novel patient-based fuzzy system that promotes the diagnosis method of asthma. The design of this application addresses five critical issues included: 1) modular representation of asthma diagnostic variables regard to patients' perception of the disease, 2) algorithmic approaches conducting inference of diagnosing based on patient's response to questions, 4) front-end mechanism for capturing data from patient, 5) output for both patient and physician regard to asthma possibility. for the system output score (0---10) the efficacy of this system calculated in the study sample included 139 asthmatic patients and 139 non-asthmatic patients (age range 6---18) reinforce the sensitivity of 88% and specificity of 100% for cut off value 0.7.