Show simple item record

dc.contributor.authorThorne C
dc.contributor.authorMontali M
dc.contributor.authorCalvanese D
dc.contributor.authorCardillo E
dc.contributor.authorEccher C
dc.contributor.editor
dc.date.accessioned2018-05-07T14:10:20Z
dc.date.available2018-05-07T14:10:20Z
dc.date.issued2013
dc.identifier.isbn978-4-9907348-0-0
dc.identifier.urihttp://aclweb.org/anthology/I/I13/I13-1160.pdf
dc.identifier.urihttp://hdl.handle.net/10863/4579
dc.descriptionPosteren_US
dc.description.abstractWe describe a first experiment on the identification and extraction of computer-interpretable guideline (CIG) components (activities, actors and consumed artifacts) from clinical documents, based on clinical entity recognition techniques. We rely on MetaMap and the UMLS Metathesaurus to provide lexical information, and study the impact of clinical document syntax and semantics on activity recognition.en_US
dc.language.isoenen_US
dc.publisherAsian Federation of Natural Language Processing / ACLen_US
dc.rights
dc.titleAutomated activity recognition in clinical documentsen_US
dc.typeBook chapteren_US
dc.date.updated2017-11-04T09:34:47Z
dc.publication.titleProceedings of the 6th International Joint Conference on Natural Language Processing (IJCNLP)
dc.language.isiEN-GB
dc.description.fulltextopenen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record