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Fuzzy Rule-Based Expert System for Assessment Severity of Asthma

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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.

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Acknowledgement

I would like to appreciate all who gave me the possibility to complete this paper. I want to thank the physicians and staff of Immunology, Asthma & Allergy Research center for their collaboration in providing necessary knowledge. I thank Dr Heydarnejad and Dr. Fazlollahi for their guidance, Mehdi Taherian for contribution in knowledge representation I appreciate Zahra Zolnoor, Ali Zolnoor, and Mohammad Reza Zolnoor for providing general information. Finally I thank Neda Kharghani for reviewing this paper and providing useful comments.

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Authors and Affiliations

  1. Department of Information Technology Management, Tarbiat Modares University, Tehran, P. O. Box 1411713116, Iran

    Maryam Zolnoori

  2. Mathematic and informatics group, Academic Center for Education, Culture and Research (ACECR), Tarbiat Modares University, Tehran, P. O. Box 14115-343, Iran

    Maryam Zolnoori

  3. Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran

    Mohammad Hossein Fazel Zarandi

  4. Immunology, Asthma and Allergy Research Institute, Tehran University of Medical Sciences, Tehran, Iran

    Mostafa Moin & Shahram Teimorian

Authors
  1. Maryam Zolnoori
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  2. Mohammad Hossein Fazel Zarandi
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  3. Mostafa Moin
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Corresponding author

Correspondence to Maryam Zolnoori.

Appendix

Appendix

In the appendix some rules related to module of asthma control system is represented.

  • Module of Respiratory symptom severity

If

Daily symptoms is sometimes

AND Nocturnal symptoms is sometimes

AND Dyspnoea is Medium_low

Then

SRS is Medium_low

  • Module of Bronchial Obstruction

If

FEV1>.90%

AND FVC>.90%

AND FEV1/FVC >.90%

Then

BO is Normal

  • Module of Asthma Instability

If

PEF is mild

AND No exacerbation

Then

Asthma Instability is low

  • Module of Quality of life

If

Miss days of school is None

AND Effect on activities is None

AND Looking for new treatment is None

Then

The SF is good

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Zolnoori, M., Zarandi, M.H.F., Moin, M. et al. Fuzzy Rule-Based Expert System for Assessment Severity of Asthma. J Med Syst 36, 1707–1717 (2012). https://doi.org/10.1007/s10916-010-9631-8

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  • DOI: https://doi.org/10.1007/s10916-010-9631-8

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