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From Smart Health to Smart Hospitals Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

Linking Biomedical Data to the Cloud

verfasst von : Stefan Zwicklbauer, Christin Seifert, Michael Granitzer

Erschienen in: Smart Health

Verlag: Springer International Publishing

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Abstract

The application of Knowledge Discovery and Data Mining approaches forms the basis of realizing the vision of Smart Hospitals. For instance, the automated creation of high-quality knowledge bases from clinical reports is important to facilitate decision making processes for clinical doctors. A subtask of creating such structured knowledge is entity disambiguation that establishes links by identifying the correct semantic meaning from a set of candidate meanings to a text fragment. This paper provides a short, concise overview of entity disambiguation in the biomedical domain, with a focus on annotated corpora (e.g. CalbC), term disambiguation algorithms (e.g. abbreviation disambiguation) as well as gene and protein disambiguation algorithms (e.g. inter-species gene name disambiguation). Finally, we provide some open problems and future challenges that we expect future research will take into account.

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Querying RefSeq database (http://​www.​ncbi.​nlm.​nih.​gov/​refseq/​). The number of species was manually counted.
 
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Metadaten
Titel
Linking Biomedical Data to the Cloud
verfasst von
Stefan Zwicklbauer
Christin Seifert
Michael Granitzer
Copyright-Jahr
2015
Buch
Smart Health

Print ISBN: 978-3-319-16225-6

Electronic ISBN: 978-3-319-16226-3

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-16226-3_9