Automated Activity Recognition in Clinical Documents

Proc. of the 6th Int. Joint Conf. on Natural Language Processing (IJCNLP 2013). 2013.

We 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.

@inproceedings{IJCNLP-2013,
   title = "Automated Activity Recognition in Clinical Documents",
   year = "2013",
   author = "Camilo Thorne and Marco Montali and Diego Calvanese and
Elena Cardillo and Claudio Eccher",
   booktitle = "Proc. of the 6th Int. Joint Conf. on Natural Language
Processing (IJCNLP 2013)",
   pages = "1129--1133",
   publisher = "Asian Federation of Natural Language Processing",
}