scholarly journals A Novel Coverage Pattern Mining Method for Unordered Tree

2017 ◽  
Vol 12 ◽  
pp. 01002
Author(s):  
Ying Xia ◽  
Hong-Xu Li
Author(s):  
Tomoyuki Morita ◽  
Yasushi Hirano ◽  
Yasuyuki Sumi ◽  
Shoji Kajita ◽  
Kenji Mase
Keyword(s):  

Author(s):  
Aleardo Junior Manacero ◽  
Renata Spolon Lobato ◽  
Marcos Antônio Cavenaghi ◽  
Alexandre Colombo ◽  
Roberta Spolon

Author(s):  
Zhengzheng Xing ◽  
Jian Pei

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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