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Fuzzy Rule Based System Approach for the prediction of Respiratory Abnormalities in Solid Waste Workers

Namrata Jariwala and R. A. Christian
Civil Engg. Department at S.V. National Institute of Technology, Surat-395007, India
Abstract—The prediction of diseases is a complex process, as it is influenced by number of factors. Medical science uses the symptoms, laboratory test and medical history of the person as diagnosis tools for prediction of diseases. In this paper, fuzzy rule-based system approach has been proposed to determine respiratory abnormalities among solid waste workers. For the prediction of diseases, studies of many biochemical parameters of healthy people with different age, BMI and habit data are required. Medical science considers the criteria of odds ratio for the study of disease occurrence pattern in which comparison is made with exposed and non-exposed group. In this paper, new proposed methodology is discussed which can determine person risk to suffer from respiratory diseases. In Fuzzy rule-based system approach, available information from medical experts is used to generate the person risk in 0 to 1 scale without any medical diagnosis or laboratory test. The determine risk value can be used to modify the factor for the occurrence of diseases in individual and preventive steps can be considered for curing of diseases before any medical diagnosis or test.

Index Terms—Fuzzy logic, respiratory diseases, risk, solid, waste workers

Cite: Namrata Jariwala and R. A. Christian, "Fuzzy Rule Based System Approach for the prediction of Respiratory Abnormalities in Solid Waste Workers," International Journal of Life Sciences Biotechnology and Pharma Research, Vol. 4, No. 1, pp. 62-65, January 2015.
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