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Gewählte Publikation:

SHR Neuro Krebs Kardio Lipid Stoffw Microb

López-García, P; Kreuzthaler, M; Schulz, S; Scherr, D; Daumke, P; Markó, K; Kors, JA; van Mulligen, EM; Wang, X; Gonna, H; Behr, E; Honrado, Á.
SEMCARE: Multilingual Semantic Search in Semi-Structured Clinical Data.
Stud Health Technol Inform. 2016; 223(3):93-99 [OPEN ACCESS]


Führende Autor*innen der Med Uni Graz
Lopez Garcia Pablo
Co-Autor*innen der Med Uni Graz
Kreuzthaler Markus Eduard
Scherr Daniel
Schulz Stefan

Dimensions Citations:

Plum Analytics:
The vast amount of clinical data in electronic health records constitutes a great potential for secondary use. However, most of this content consists of unstructured or semi-structured texts, which is difficult to process. Several challenges are still pending: medical language idiosyncrasies in different natural languages, and the large variety of medical terminology systems. In this paper we present SEMCARE, a European initiative designed to minimize these problems by providing a multi-lingual platform (English, German, and Dutch) that allows users to express complex queries and obtain relevant search results from clinical texts. SEMCARE is based on a selection of adapted biomedical terminologies, together with Apache UIMA and Apache Solr as open source state-of-the-art natural language pipeline and indexing technologies. SEMCARE has been deployed and is currently being tested at three medical institutions in the UK, Austria, and the Netherlands, showing promising results in a cardiology use case.
Find related publications in this database (using NLM MeSH Indexing)
Data Mining - methods
Electronic Health Records -
Humans -
Information Storage and Retrieval - methods
Language -
Linguistics - methods
Natural Language Processing -
Semantics -

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