We describe a first experiment on automated activity and relation identication, and more in general, on the automated identication and extraction of computer-interpretable guideline fragments from clinical documents. We rely on clinical entity and relation (activities, actors, artifacts and their relations) recognition techniques and use MetaMap and the UMLS Metathesaurus to provide lexical information. In particular, we study the impact of clinical document syntax and semantics on the precision of activity and temporal relation recognition.
Process Fragment Recognition in Clinical Documents
Cardillo, Elena;Eccher, Claudio;
2013-01-01
Abstract
We describe a first experiment on automated activity and relation identication, and more in general, on the automated identication and extraction of computer-interpretable guideline fragments from clinical documents. We rely on clinical entity and relation (activities, actors, artifacts and their relations) recognition techniques and use MetaMap and the UMLS Metathesaurus to provide lexical information. In particular, we study the impact of clinical document syntax and semantics on the precision of activity and temporal relation recognition.File in questo prodotto:
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