Identifying Air Pollution Risk Factors for Respiratory Disease Using Quantitative Computational Method
International Journal of Biomedical Science and Engineering
Volume 5, Issue 3, June 2017, Pages: 18-23
Received: May 4, 2017; Published: May 5, 2017
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Authors
Songjing Chen, Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing, China
Sizhu Wu, Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing, China
Qing Qian, Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing, China
Jiao Li, Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing, China
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Abstract
In order to identify air pollution risk factors for respiratory disease patients, a quantitative computational method to identify high risk factors for respiratory patients was conducted in this study. The C4.5 classification algorithm was used in the computational method. SMOTE algorithm was applied to solve the imbalance data problem. Risk factor effect degree was calculated according to C4.5 classification model. Age was the top risk factor in nine subgroups, except ≤11. The age ≤49 youth were easier affected by NO2 and SO2 than >49. ≤49 were obviously more than >49. ≤49 were more easier suffer from acute upper respiratory infections, >49 were more easier suffer from influenza, pneumonia and chronic lower respiratory disease. The air pollution risk factors of respiratory disease were identified quantitatively. This quantitative computational method could be applied to predict other disease occurrence.
Keywords
Respiratory Disease, Air Pollutant, C4.5 Classification Algorithm, Data Mining
To cite this article
Songjing Chen, Sizhu Wu, Qing Qian, Jiao Li, Identifying Air Pollution Risk Factors for Respiratory Disease Using Quantitative Computational Method, International Journal of Biomedical Science and Engineering. Vol. 5, No. 3, 2017, pp. 18-23. doi: 10.11648/j.ijbse.20170503.11
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