A Case-Based-Reasoning System for Feature Selection and Diagnosing Asthma

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Author(s): Somayeh Akhavan Darabi (Azad University of Tehran Shomal, Iran)and Babak Teimourpour (Tarbiat Modares University, Iran)
Copyright: 2017
Pages: 16
Source title: Handbook of Research on Data Science for Effective Healthcare Practice and Administration
Source Author(s)/Editor(s): Elham Akhond Zadeh Noughabi (University of Calgary, Canada), Bijan Raahemi (University of Ottawa, Canada), Amir Albadvi (Tarbiat Modares University, Iran)and Behrouz H. Far (University of Calgary, Canada)
DOI: 10.4018/978-1-5225-2515-8.ch019

Keywords: Business & Management / Business Science Reference / Decision Support Systems / Healthcare Administration

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Abstract

Asthma is a chronic disease of the airways in the lungs. The differentiation between asthma, COPD and bronchiectasis in the early stage of disease is very important for the adoption of appropriate therapeutic measures. In this research, a case-based-reasoning (CBR) model is proposed to assist a physician to therapy. First of all, features and symptoms are determined and patients' data is gathered with a questionnaire, then CBR algorithm is run on the data which leads to the asthma diagnosis. The system was tested on 325 asthmatic and non-asthmatic adult cases and the accuracy was eighty percent. The consequences were promising. This study was performed in order to determine risk factors for asthma in a specific society and the results of research showed that the most important variables of asthma disease are symptoms hyper-responsive, frequency of cough and cough.

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A Case-Based-Reasoning System for Feature Selection and Diagnosing Asthma

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