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Journal of Medical Systems

Erschienen in:

01.06.2012 | ORIGINAL PAPER

Fuzzy Rule-Based Expert System for Assessment Severity of Asthma

verfasst von: Maryam Zolnoori, Mohammad Hossein Fazel Zarandi, Mostafa Moin, Shahram Teimorian

Erschienen in: Journal of Medical Systems | Ausgabe 3/2012

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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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Titel: Fuzzy Rule-Based Expert System for Assessment Severity of Asthma
verfasst von: Maryam Zolnoori
Mohammad Hossein Fazel Zarandi
Mostafa Moin
Shahram Teimorian
Publikationsdatum: 01.06.2012
Verlag: Springer US
Erschienen in: Journal of Medical Systems / Ausgabe 3/2012
Print ISSN: 0148-5598
Elektronische ISSN: 1573-689X
DOI: https://doi.org/10.1007/s10916-010-9631-8

Springer Medizin

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