Analysis of Semantically Enriched Process Data for Identifying Process-Biomarkers release_ehljqmbsjbgffnk2xwqiplb4ri

by Tobias Weller, Maria Maleshkova, Martin Wagner, Lena-Marie Ternes, Hannes Kenngott

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Abstract

Intelligent data analysis is used in multiple domains to find new insights in data that has not been known before. Among others, intelligent data analysis is used in the health-care 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 for identifying Process-Biomarkers in medical treatment processes. The semantics allow 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.
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