Title: Asthma diagnosis and level of control using decision tree and fuzzy system

Authors: Aman Tyagi; Preetvanti Singh

Addresses: Dayalbagh Educational Institute, Dayalbagh, Agra 282005, India ' Dayalbagh Educational Institute, Dayalbagh, Agra 282005, India

Abstract: Asthma is a chronic lung disease caused due to shorten airway path of the patient. Development of a symptom-based decision support system will help in effective diagnosis, which is the focus of this paper. In this paper first phase is to diagnose asthma using data mining tools and in the second phase asthma control level is measured using fuzzy inference system. The diagnosis is based on the symptoms like sneezing, dry cough, sore throat etc. The asthma level of control is based on the symptoms like shortness of breath, limitation of activities, day time symptoms etc. Finally accuracy of the system and value of kappa coefficient is computed and reported here.

Keywords: asthma diagnosis; data mining; fuzzy inference system; decision tree; fuzzy membership function; Mamdani-type FIS; fuzzy rules; expert systems; biomedical engineering; fuzzy logic; decision support systems; DSS; asthma control level; asthma symptoms.

DOI: 10.1504/IJBET.2014.065658

International Journal of Biomedical Engineering and Technology, 2014 Vol.16 No.2, pp.169 - 181

Received: 10 Apr 2014
Accepted: 18 Aug 2014
Published online: 25 Apr 2015 *

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