KOPS - Das Institutionelle Repositorium der Universität Konstanz

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

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

Zitieren

Dateien zu dieser Ressource

Dateien Größe Format Anzeige

Zu diesem Dokument gibt es keine Dateien.

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 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). Wuhan, 18. Okt 2014 - 19. Okt 2014. IEEE, pp. 389-394. ISBN 978-1-4799-5352-3

@inproceedings{Huang2014Medic-30286, title={Medical social media analytics via ranking and big learning : an image-based disease prediction study}, year={2014}, doi={10.1109/SPAC.2014.6982722}, 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} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/30286"> <dc:contributor>Huang, Wei</dc:contributor> <dc:creator>Shen, Minmin</dc:creator> <dc:language>eng</dc:language> <dc:creator>Zhang, Peng</dc:creator> <dc:contributor>Zhang, Peng</dc:contributor> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/30286"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2015-03-16T10:02:15Z</dcterms:available> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2015-03-16T10:02:15Z</dc:date> <dcterms:abstract xml:lang="eng">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.</dcterms:abstract> <dc:creator>Huang, Wei</dc:creator> <dcterms:issued>2014</dcterms:issued> <dcterms:title>Medical social media analytics via ranking and big learning : an image-based disease prediction study</dcterms:title> <dc:contributor>Shen, Minmin</dc:contributor> </rdf:Description> </rdf:RDF>

Das Dokument erscheint in:

KOPS Suche


Stöbern

Mein Benutzerkonto