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Exploring Disease Association from the NHANES Data: Data Mining, Pattern Summarization, and Visual Analytics

Exploring Disease Association from the NHANES Data: Data Mining, Pattern Summarization, and Visual Analytics

Zhengzheng Xing, Jian Pei
Copyright: © 2012 |Pages: 17
ISBN13: 9781613504741|ISBN10: 1613504748|EISBN13: 9781613504758
DOI: 10.4018/978-1-61350-474-1.ch010
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MLA

Xing, Zhengzheng, and Jian Pei. "Exploring Disease Association from the NHANES Data: Data Mining, Pattern Summarization, and Visual Analytics." Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends, edited by David Taniar and Lukman Hakim Iwan, IGI Global, 2012, pp. 157-173. https://doi.org/10.4018/978-1-61350-474-1.ch010

APA

Xing, Z. & Pei, J. (2012). Exploring Disease Association from the NHANES Data: Data Mining, Pattern Summarization, and Visual Analytics. In D. Taniar & L. Iwan (Eds.), Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends (pp. 157-173). IGI Global. https://doi.org/10.4018/978-1-61350-474-1.ch010

Chicago

Xing, Zhengzheng, and Jian Pei. "Exploring Disease Association from the NHANES Data: Data Mining, Pattern Summarization, and Visual Analytics." In Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends, edited by David Taniar and Lukman Hakim Iwan, 157-173. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-61350-474-1.ch010

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Abstract

Finding associations among different diseases is an important task in medical data mining. The NHANES data is a valuable source in exploring disease associations. However, existing studies analyzing the NHANES data focus on using statistical techniques to test a small number of hypotheses. This NHANES data has not been systematically explored for mining disease association patterns. In this regard, this paper proposes a direct disease pattern mining method and an interactive disease pattern mining method to explore the NHANES data. The results on the latest NHANES data demonstrate that these methods can mine meaningful disease associations consistent with the existing knowledge and literatures. Furthermore, this study provides summarization of the data set via a disease influence graph and a disease hierarchical tree.

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