Paper Info
Title
Research on intelligent extraction of literature knowledge for the risk factors of chronic diseases.
Abstract
Medical literature research results are more accurate and representative than patient medical record data. The medical literature intelligently extracts research objects, research areas, and research result entities, identifies their indexing features in the abstract, and finds risk factors for chronic illness and its association with regions and populations. This study proposes a literature knowledge extraction model for chronic disease risk factors. Based on dictionaries and rules, manual annotation extraction methods and gCLUTO dual cluster analysis, the Chinese biomedical literature database was published to correlate with chronic disease risk factors. The literature is a corpus, which intelligently identifies extracts and clusters the literature abstracts. The discovery of chronic disease risk factors from the perspective of human health was explored by taking the literature of hypertension risk factor research as an example; the literature knowledge extraction model for chronic disease risk factors was verified to construct a chronic disease risk factor set. It also reveals the relationship between chronic disease risk factors and regions/populations, and provides reference and reference for the research of chronic disease risk factors.
Year
DOI
Venue
2020
10.3233/JIFS-179786
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
DocType
Volume
Chronic disease,risk factors,intelligent extraction,knowledge discovery
Journal
38
Issue
ISSN
Citations 
SP6
1064-1246
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Jing Wang100.34
Xiaobo Tang200.34
Qian Huang300.34