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| + | |Abstract=Intelligent data analysis is used in multiple domains to find new insights in the data that has not been known before. Among others, intelligent data analysis is used in the healthcare sector to analyse patient and process data for discovering conclusions and supporting the decison-making process. Besides this, Semantic Web Technologies are currently finding new and broader application areas, including the medical domain. We want to use the advantages of semantic technologies in our data analysis to identify Process-Biomarkers in medical treatment processes. The semantics allows for a more efficient retrieval of arduous and complex requests, which enables a more intelligent data analysis. This allows for identifying and quantifying effects between different performed tasks and events in medical treatment processes in a more detailed way. To address this we 1) extracted information from different data sources; 2) applied Semantic Web Technologies on the extracted information and integrated them into a collaborative platform and enriched them with further semantic background knowledge; 3) performed different statistical methods on the semantically enriched data to identify Process-Biomarkers. | ||
|ISBN=978-1-61208-518-0 | |ISBN=978-1-61208-518-0 | ||
|ISSN=2308-4065 | |ISSN=2308-4065 | ||
|Forschungsgruppe=Web Science und Wissensmanagement | |Forschungsgruppe=Web Science und Wissensmanagement | ||
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Version vom 30. August 2016, 08:52 Uhr
Analysis of Semantically Enriched Process Data for Identifying Process-Biomarkers
Analysis of Semantically Enriched Process Data for Identifying Process-Biomarkers
Published: 2016
November
Buchtitel: Proceedings INTELLI
Seiten: 6
Verlag: IARIA XPS Press
Referierte Veröffentlichung
BibTeX
Kurzfassung
Intelligent data analysis is used in multiple domains to find new insights in the data that has not been known before. Among others, intelligent data analysis is used in the healthcare sector to analyse patient and process data for discovering conclusions and supporting the decison-making process. Besides this, Semantic Web Technologies are currently finding new and broader application areas, including the medical domain. We want to use the advantages of semantic technologies in our data analysis to identify Process-Biomarkers in medical treatment processes. The semantics allows for a more efficient retrieval of arduous and complex requests, which enables a more intelligent data analysis. This allows for identifying and quantifying effects between different performed tasks and events in medical treatment processes in a more detailed way. To address this we 1) extracted information from different data sources; 2) applied Semantic Web Technologies on the extracted information and integrated them into a collaborative platform and enriched them with further semantic background knowledge; 3) performed different statistical methods on the semantically enriched data to identify Process-Biomarkers.
ISBN: 978-1-61208-518-0
ISSN: 2308-4065
Web Science und Wissensmanagement