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IASM: A System for the Intelligent Active Surveillance of Malaria
Joint Authors
Wang, Xinlei
Yang, Bo
Huang, Jing
Chen, Hechang
Gu, Xiao
Bai, Yuan
Du, Zhanwei
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-07-31
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Malaria, a life-threatening infectious disease, spreads rapidly via parasites.
Malaria prevention is more effective and efficient than treatment.
However, the existing surveillance systems used to prevent malaria are inadequate, especially in areas with limited or no access to medical resources.
In this paper, in order to monitor the spreading of malaria, we develop an intelligent surveillance system based on our existing algorithms.
First, a visualization function and active surveillance were implemented in order to predict and categorize areas at high risk of infection.
Next, socioeconomic and climatological characteristics were applied to the proposed prediction model.
Then, the redundancy of the socioeconomic attribute values was reduced using the stepwise regression method to improve the accuracy of the proposed prediction model.
The experimental results indicated that the proposed IASM predicted malaria outbreaks more close to the real data and with fewer variables than other models.
Furthermore, the proposed model effectively identified areas at high risk of infection.
American Psychological Association (APA)
Wang, Xinlei& Yang, Bo& Huang, Jing& Chen, Hechang& Gu, Xiao& Bai, Yuan…[et al.]. 2016. IASM: A System for the Intelligent Active Surveillance of Malaria. Computational and Mathematical Methods in Medicine،Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1100075
Modern Language Association (MLA)
Wang, Xinlei…[et al.]. IASM: A System for the Intelligent Active Surveillance of Malaria. Computational and Mathematical Methods in Medicine No. 2016 (2016), pp.1-11.
https://search.emarefa.net/detail/BIM-1100075
American Medical Association (AMA)
Wang, Xinlei& Yang, Bo& Huang, Jing& Chen, Hechang& Gu, Xiao& Bai, Yuan…[et al.]. IASM: A System for the Intelligent Active Surveillance of Malaria. Computational and Mathematical Methods in Medicine. 2016. Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1100075
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1100075