| dc.contributor.author | Starlinger, Johannes | |
| dc.contributor.author | Kittner, Madeleine | |
| dc.contributor.author | Blankenstein, Oliver | |
| dc.contributor.author | Leser, Ulf | |
| dc.date.accessioned | 2018-04-12T12:50:39Z | |
| dc.date.available | 2018-04-12T12:50:39Z | |
| dc.date.issued | 2017 | |
| dc.identifier.issn | 1611-2776 | |
| dc.identifier.uri | http://dl.gi.de/handle/20.500.12116/16388 | |
| dc.description.abstract | Vast amounts of medical information are still recorded as unstructured text. The knowledge contained in this textual data has a great potential to improve clinical routine care, to support clinical research, and to advance personalization of medicine. To access this knowledge, the underlying data has to be semantically integrated – an essential prerequisite to which is information extraction from clinical documents. | en |
| dc.language.iso | en | |
| dc.publisher | De Gruyter | |
| dc.relation.ispartof | it - Information Technology: Vol. 59, No. 5 | |
| dc.subject | Medical text mining | |
| dc.subject | information extraction | |
| dc.subject | semantic information integration | |
| dc.title | How to improve information extraction from German medical records | en |
| dc.type | Text/Journal Article | |
| dc.pubPlace | Berlin | |
| mci.reference.pages | 171 | |
| mci.conference.sessiontitle | Thematic Issue: Multicore technology in the mobility domains | |
| dc.identifier.doi | 10.1515/itit-2016-0027 | |
