The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services

Dharmendra Sharma; Fariba Shadabi

doi:10.1109/BDCloud.2014.25

The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services

Dharmendra Sharma, Fariba Shadabi

AI and Robotics

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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.

Original language	English
Title of host publication	2014 IEEE Fourth International Conference on Big Data and Cloud Computing
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	350-354
Number of pages	5
ISBN (Print)	9781479967193
DOIs	https://doi.org/10.1109/BDCloud.2014.25
Publication status	Published - 5 Dec 2014
Event	2014 IEEE Fourth International Conference on Big Data and Cloud Computing - Sydney, NSW, Australia Duration: 3 Dec 2014 → 5 Dec 2014

Conference

Conference	2014 IEEE Fourth International Conference on Big Data and Cloud Computing
Period	3/12/14 → 5/12/14

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10.1109/BDCloud.2014.25

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7034815

Cite this

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title = "The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services",

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.",

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author = "Dharmendra Sharma and Fariba Shadabi",

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booktitle = "2014 IEEE Fourth International Conference on Big Data and Cloud Computing",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

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note = "2014 IEEE Fourth International Conference on Big Data and Cloud Computing ; Conference date: 03-12-2014 Through 05-12-2014",

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Sharma, D & Shadabi, F 2014, The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services. in 2014 IEEE Fourth International Conference on Big Data and Cloud Computing., 7034815, IEEE, Institute of Electrical and Electronics Engineers, pp. 350-354, 2014 IEEE Fourth International Conference on Big Data and Cloud Computing, 3/12/14. https://doi.org/10.1109/BDCloud.2014.25

The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services. / Sharma, Dharmendra; Shadabi, Fariba.
2014 IEEE Fourth International Conference on Big Data and Cloud Computing. IEEE, Institute of Electrical and Electronics Engineers, 2014. p. 350-354 7034815.

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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N2 - 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.

AB - 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.

KW - Data mining

KW - Medical services

KW - Informatics

KW - Big data

KW - Kidney

KW - Databases

KW - Educational institutions

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M3 - Conference contribution

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BT - 2014 IEEE Fourth International Conference on Big Data and Cloud Computing

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - 2014 IEEE Fourth International Conference on Big Data and Cloud Computing

Y2 - 3 December 2014 through 5 December 2014

ER -

The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services

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