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Selected Publication:

SHR Neuro Cancer Cardio Lipid Metab Microb

Kreuzthaler, M; Daumke, P; Schulz, S.
Semantic retrieval and navigation in clinical document collections.
Stud Health Technol Inform. 2015; 212(3):9-14
PubMed

 

Leading authors Med Uni Graz
Kreuzthaler Markus Eduard
Co-authors Med Uni Graz
Schulz Stefan
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Abstract:
Patients with chronic diseases undergo numerous in- and outpatient treatment periods, and therefore many documents accumulate in their electronic records. We report on an on-going project focussing on the semantic enrichment of medical texts, in order to support recall-oriented navigation across a patient's complete documentation. A document pool of 1,696 de-identified discharge summaries was used for prototyping. A natural language processing toolset for document annotation (based on the text-mining framework UIMA) and indexing (Solr) was used to support a browser-based platform for document import, search and navigation. The integrated search engine combines free text and concept-based querying, supported by dynamically generated facets (diagnoses, procedures, medications, lab values, and body parts). The prototype demonstrates the feasibility of semantic document enrichment within document collections of a single patient. Originally conceived as an add-on for the clinical workplace, this technology could also be adapted to support personalised health record platforms, as well as cross-patient search for cohort building and other secondary use scenarios.
Find related publications in this database (using NLM MeSH Indexing)
Data Mining - methods
Electronic Health Records - organization & administration
Machine Learning -
Natural Language Processing -
Semantics -
Software -
User-Computer Interface -
Vocabulary, Controlled -
Web Browser -

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