This paper presents the evaluation of the dictionary look-up component of Mayo Clinic's Information Extraction system. The component was tested on a corpus of 160 free-text c...
Karin Schuler, Vinod Kaggal, James J. Masanz, Phil...
This paper presents ongoing research in clinical information extraction. This work introduces a new genre of text which are not well-written, noise prone, ungrammatical and with m...
We describe the semi-automatic adaptation of a TimeML annotated corpus from English to Portuguese, a language for which TimeML annotated data was not available yet. In order to va...
As more and more information is available in the Electronic Health Record in the form of free-text narrative, there is a need for automated tools, which can process and understand...
This paper reports on the annotation of a corpus of 1 million words with four semantic annotation layers, including named entities, coreference relations, semantic roles and spati...