DocumentCode :
262409
Title :
The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services
Author :
Sharma, Dharmendra ; Shadabi, Fariba
Author_Institution :
Fac. of Educ., Sci., Technol. & Math., Univ. of Canberra, Canberra, ACT, Australia
fYear :
2014
fDate :
3-5 Dec. 2014
Firstpage :
350
Lastpage :
354
Abstract :
Social and health informatics has the potential of improving the general wellbeing and health of individuals. Although the structure and nature of health facilities and services in some countries may pose a challenge for a short while, such obstacles according to many studies will be streamlined in the near future. The widespread utilization and implementation of healthcare information system in the day-to-day health care operations will lead to cost effective clinical trials and self-healthcare management. On the other hand, recent rapid development of computer technology in this area has introduced a data explosion challenge. This paper provides brief background information on Social Informatics and e-Health Systems. Follow by an overview of two hybrid intelligent techniques that might be utilized as a new generation of predictive analytics for big data particularly for knowledge discovery in big data and decision making processes in social systems.
Keywords :
Big Data; data analysis; data mining; decision making; health care; medical computing; medical information systems; multi-agent systems; social sciences computing; big data; computer technology; cost effective clinical trials; data explosion challenge; day-to-day health care operations; decision making process; e-health service improvement; e-health systems; general wellbeing improvement; health informatics; healthcare information system; hybrid data mining approach; hybrid intelligent techniques; knowledge discovery; multiagent approach; predictive analytics generation; self-healthcare management; social informatics; social systems; Big data; Data mining; Databases; Educational institutions; Informatics; Kidney; Medical services; Multi-agents; hybrid algorithm; real time analysis and data mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on
Conference_Location :
Sydney, NSW
Type :
conf
DOI :
10.1109/BDCloud.2014.25
Filename :
7034815
Link To Document :
بازگشت