Mining heterogeneous information graph for health status classification
Paper
Paper/Presentation Title | Mining heterogeneous information graph for health status classification |
---|---|
Presentation Type | Paper |
Authors | Pham, Thuan (Author), Tao, Xiaohui (Author), Zhang, Ji (Author), Yong, Jianming (Author), Zhang, Wenping (Author) and Cai, Yi (Author) |
Journal or Proceedings Title | Proceedings of the 5th International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC 2018) |
Number of Pages | 6 |
Year | 2018 |
Place of Publication | United States |
ISBN | 9781728102078 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/BESC.2018.8697292 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/document/8697292 |
Web Address (URL) of Conference Proceedings | https://ieeexplore.ieee.org/xpl/conhome/8683941/proceeding |
Conference/Event | 5th International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC 2018) |
Event Details | 5th International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC 2018) Parent International Conference on Behavioral, Economic and Socio-cultural Computing (BESC) Event Date 12 to end of 14 Nov 2018 Event Location Kaohsiung, Taiwan |
Abstract | In the medical domain, there exists a large volume of data from multiple sources such as electronic health records, general health examination results, and surveys. The data contain useful information reflecting people’s health and provides great opportunities for studies to improve the quality of healthcare. However, how to mine these data effectively and efficiently still remains a critical challenge. In this paper, we propose an innovative classification model for knowledge discovery from patients’ personal health repositories. By based on analytics of massive data in the National Health and Nutrition Examination Survey, the study builds a classification model to classify patients’health status and reveal the specific disease potentially suffered by the patient. This paper makes significant contributions to the advancement of knowledge in data mining with an innovative classification model specifically crafted for domain-based data. Moreover, this research contributes to the healthcare community by providing a deep understanding of people’s health with accessibility to the patterns in various observations. |
Keywords | heterogeneous information graph, classification, healthcare |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
460208. Natural language processing | |
461299. Software engineering not elsewhere classified | |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | School of Management and Enterprise |
School of Agricultural, Computational and Environmental Sciences | |
Renmin University of China, China | |
South China University of Technology, China | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q50y5/mining-heterogeneous-information-graph-for-health-status-classification
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