Medical social media analytics via ranking and big learning : an image-based disease prediction study
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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, Wei, Peng ZHANG, Minmin SHEN, 2014. Medical social media analytics via ranking and big learning : an image-based disease prediction study. IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). Wuhan, 18. Okt. 2014 - 19. Okt. 2014. In: IEEE, , ed.. Proceedings 2014 : IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) ; October 18-19 , 2014 Wuhan, Hubei, China. IEEE, 2014, pp. 389-394. ISBN 978-1-4799-5352-3. Available under: doi: 10.1109/SPAC.2014.6982722BibTex
@inproceedings{Huang2014Medic-30286, year={2014}, doi={10.1109/SPAC.2014.6982722}, title={Medical social media analytics via ranking and big learning : an image-based disease prediction study}, isbn={978-1-4799-5352-3}, publisher={IEEE}, booktitle={Proceedings 2014 : IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) ; October 18-19 , 2014 Wuhan, Hubei, China}, pages={389--394}, editor={IEEE}, author={Huang, Wei and Zhang, Peng and Shen, Minmin} }
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