Medical social media analytics via ranking and big learning: An image-based disease prediction study

Wei Huang; Peng Zhang; Minmin Shen

doi:10.1109/SPAC.2014.6982722

Medical social media analytics via ranking and big learning: An image-based disease prediction study

Wei Huang, Peng Zhang, Minmin Shen

School of Computer Science

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

1 Scopus citations

Abstract

Medical social media analytics becomes more and more popular nowadays because of its effectiveness in benefiting diverse health-care applications. In this study, the essential disease prediction task is investigated and realized via medical social media analytics techniques. To be specific, arterial spin labeling (ASL), an emerging functional magnetic resonance imaging modality, is utilized to provide image-based information and novel ranking as well as learning techniques are proposed and incorporated to fulfill the disease prediction task in dementia. To demonstrate its superiority, comprehensive statistical experiments are conducted with comparison to several conventional methods. Promising results are reported from this study.

Original language	English
Title of host publication	Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	389-394
Number of pages	6
ISBN (Electronic)	9781479953530
DOIs	https://doi.org/10.1109/SPAC.2014.6982722
State	Published - 11 Dec 2014
Event	2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014 - Wuhan, Hubei, China Duration: 18 Oct 2014 → 19 Oct 2014

Publication series

Name	Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014

Conference

Conference	2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014
Country/Territory	China
City	Wuhan, Hubei
Period	18/10/14 → 19/10/14

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10.1109/SPAC.2014.6982722

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Huang, W., Zhang, P., & Shen, M. (2014). Medical social media analytics via ranking and big learning: An image-based disease prediction study. In Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014 (pp. 389-394). Article 6982722 (Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPAC.2014.6982722

Huang, Wei ; Zhang, Peng ; Shen, Minmin. / Medical social media analytics via ranking and big learning : An image-based disease prediction study. Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 389-394 (Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014).

@inproceedings{091409c7c565447789b41f84d10310b6,

title = "Medical social media analytics via ranking and big learning: An image-based disease prediction study",

abstract = "Medical social media analytics becomes more and more popular nowadays because of its effectiveness in benefiting diverse health-care applications. In this study, the essential disease prediction task is investigated and realized via medical social media analytics techniques. To be specific, arterial spin labeling (ASL), an emerging functional magnetic resonance imaging modality, is utilized to provide image-based information and novel ranking as well as learning techniques are proposed and incorporated to fulfill the disease prediction task in dementia. To demonstrate its superiority, comprehensive statistical experiments are conducted with comparison to several conventional methods. Promising results are reported from this study.",

author = "Wei Huang and Peng Zhang and Minmin Shen",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014 ; Conference date: 18-10-2014 Through 19-10-2014",

year = "2014",

month = dec,

day = "11",

doi = "10.1109/SPAC.2014.6982722",

language = "英语",

series = "Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "389--394",

booktitle = "Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014",

}

Huang, W, Zhang, P & Shen, M 2014, Medical social media analytics via ranking and big learning: An image-based disease prediction study. in Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014., 6982722, Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014, Institute of Electrical and Electronics Engineers Inc., pp. 389-394, 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014, Wuhan, Hubei, China, 18/10/14. https://doi.org/10.1109/SPAC.2014.6982722

Medical social media analytics via ranking and big learning: An image-based disease prediction study. / Huang, Wei; Zhang, Peng; Shen, Minmin.
Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 389-394 6982722 (Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014).

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

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AB - Medical social media analytics becomes more and more popular nowadays because of its effectiveness in benefiting diverse health-care applications. In this study, the essential disease prediction task is investigated and realized via medical social media analytics techniques. To be specific, arterial spin labeling (ASL), an emerging functional magnetic resonance imaging modality, is utilized to provide image-based information and novel ranking as well as learning techniques are proposed and incorporated to fulfill the disease prediction task in dementia. To demonstrate its superiority, comprehensive statistical experiments are conducted with comparison to several conventional methods. Promising results are reported from this study.

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Huang W, Zhang P, Shen M. Medical social media analytics via ranking and big learning: An image-based disease prediction study. In Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 389-394. 6982722. (Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2014). doi: 10.1109/SPAC.2014.6982722

Medical social media analytics via ranking and big learning: An image-based disease prediction study

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