Dynamic creation of social networks for syndromic surveillance using information fusion

Jared Holsopple; Shanchieh Yang; Moises Sudit; Adam Stotz

doi:10.1007/978-3-642-12079-4_41

Dynamic creation of social networks for syndromic surveillance using information fusion

Jared Holsopple
, Shanchieh Yang
, Moises Sudit
, Adam Stotz

Department of Industrial and Systems Engineering

CUBRC
Rochester Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

To enhance the effectiveness of health care, many medical institutions have started transitioning to electronic health and medical records and sharing these records between institutions. The large amount of complex and diverse data makes it difficult to identify and track relationships and trends, such as disease outbreaks, from the data points. INFERD: Information Fusion Engine for Real-Time Decision-Making is an information fusion tool that dynamically correlates and tracks event progressions. This paper presents a methodology that utilizes the efficient and flexible structure of INFERD to create social networks representing progressions of disease outbreaks. Individual symptoms are treated as features allowing multiple hypothesis being tracked and analyzed for effective and comprehensive syndromic surveillance.

Original language	English
Title of host publication	Advances in Social Computing - Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, Proceedings
Pages	330-337
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-12079-4_41
State	Published - 2010
Event	3rd International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010 - Bethesda, MD, United States Duration: Mar 30 2010 → Mar 31 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6007 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010
Country/Territory	United States
City	Bethesda, MD
Period	03/30/10 → 03/31/10

Keywords

Disease outbreak prevention
Information fusion
Social networks
Syndromic surveillance

Access to Document

10.1007/978-3-642-12079-4_41

Cite this

Holsopple, J., Yang, S., Sudit, M., & Stotz, A. (2010). Dynamic creation of social networks for syndromic surveillance using information fusion. In Advances in Social Computing - Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, Proceedings (pp. 330-337). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6007 LNCS). https://doi.org/10.1007/978-3-642-12079-4_41

Holsopple, Jared ; Yang, Shanchieh ; Sudit, Moises et al. / Dynamic creation of social networks for syndromic surveillance using information fusion. Advances in Social Computing - Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, Proceedings. 2010. pp. 330-337 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Dynamic creation of social networks for syndromic surveillance using information fusion",

abstract = "To enhance the effectiveness of health care, many medical institutions have started transitioning to electronic health and medical records and sharing these records between institutions. The large amount of complex and diverse data makes it difficult to identify and track relationships and trends, such as disease outbreaks, from the data points. INFERD: Information Fusion Engine for Real-Time Decision-Making is an information fusion tool that dynamically correlates and tracks event progressions. This paper presents a methodology that utilizes the efficient and flexible structure of INFERD to create social networks representing progressions of disease outbreaks. Individual symptoms are treated as features allowing multiple hypothesis being tracked and analyzed for effective and comprehensive syndromic surveillance.",

keywords = "Disease outbreak prevention, Information fusion, Social networks, Syndromic surveillance",

author = "Jared Holsopple and Shanchieh Yang and Moises Sudit and Adam Stotz",

year = "2010",

doi = "10.1007/978-3-642-12079-4\_41",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "330--337",

booktitle = "Advances in Social Computing - Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, Proceedings",

note = "3rd International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010 ; Conference date: 30-03-2010 Through 31-03-2010",

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Holsopple, J, Yang, S, Sudit, M & Stotz, A 2010, Dynamic creation of social networks for syndromic surveillance using information fusion. in Advances in Social Computing - Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6007 LNCS, pp. 330-337, 3rd International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, Bethesda, MD, United States, 03/30/10. https://doi.org/10.1007/978-3-642-12079-4_41

Dynamic creation of social networks for syndromic surveillance using information fusion. / Holsopple, Jared; Yang, Shanchieh; Sudit, Moises et al.
Advances in Social Computing - Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, Proceedings. 2010. p. 330-337 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6007 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Dynamic creation of social networks for syndromic surveillance using information fusion

AU - Holsopple, Jared

AU - Yang, Shanchieh

AU - Sudit, Moises

AU - Stotz, Adam

PY - 2010

Y1 - 2010

N2 - To enhance the effectiveness of health care, many medical institutions have started transitioning to electronic health and medical records and sharing these records between institutions. The large amount of complex and diverse data makes it difficult to identify and track relationships and trends, such as disease outbreaks, from the data points. INFERD: Information Fusion Engine for Real-Time Decision-Making is an information fusion tool that dynamically correlates and tracks event progressions. This paper presents a methodology that utilizes the efficient and flexible structure of INFERD to create social networks representing progressions of disease outbreaks. Individual symptoms are treated as features allowing multiple hypothesis being tracked and analyzed for effective and comprehensive syndromic surveillance.

AB - To enhance the effectiveness of health care, many medical institutions have started transitioning to electronic health and medical records and sharing these records between institutions. The large amount of complex and diverse data makes it difficult to identify and track relationships and trends, such as disease outbreaks, from the data points. INFERD: Information Fusion Engine for Real-Time Decision-Making is an information fusion tool that dynamically correlates and tracks event progressions. This paper presents a methodology that utilizes the efficient and flexible structure of INFERD to create social networks representing progressions of disease outbreaks. Individual symptoms are treated as features allowing multiple hypothesis being tracked and analyzed for effective and comprehensive syndromic surveillance.

KW - Disease outbreak prevention

KW - Information fusion

KW - Social networks

KW - Syndromic surveillance

UR - https://www.scopus.com/pages/publications/78650389217

U2 - 10.1007/978-3-642-12079-4_41

DO - 10.1007/978-3-642-12079-4_41

M3 - Conference contribution

AN - SCOPUS:78650389217

SN - 3642120784

SN - 9783642120787

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 330

EP - 337

BT - Advances in Social Computing - Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, Proceedings

T2 - 3rd International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010

Y2 - 30 March 2010 through 31 March 2010

ER -

Holsopple J, Yang S, Sudit M, Stotz A. Dynamic creation of social networks for syndromic surveillance using information fusion. In Advances in Social Computing - Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, Proceedings. 2010. p. 330-337. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-12079-4_41

Dynamic creation of social networks for syndromic surveillance using information fusion

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Keywords

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