{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:40:35Z","timestamp":1758271235499},"reference-count":5,"publisher":"Walter de Gruyter GmbH","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,8,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Vast amounts of medical information are still recorded as unstructured text. The knowledge contained in this textual data\nhas a great potential to improve clinical routine care, to support clinical research, and to advance personalization of\nmedicine. To access this knowledge, the underlying data has to be semantically integrated \u2013 an essential prerequisite to\nwhich is information extraction from clinical documents.<\/jats:p>\n               <jats:p>A body of work, and a good selection of openly available tools for information extraction and semantic integration in the\nmedical domain exist, yet almost exclusively for English language documents. For German texts the situation is rather\ndifferent: research work is sparse, tools are proprietary or unpublished, and rarely any freely available textual\nresources exist. In this survey, we (1) describe the challenges of information extraction from German medical documents\nand the hurdles posed to research in this area, (2) especially address the problems of missing German language resources\nand privacy implications, and (3) identify the steps necessary to overcome these hurdles and fuel research in semantic\nintegration of textual clinical data.<\/jats:p>","DOI":"10.1515\/itit-2016-0027","type":"journal-article","created":{"date-parts":[[2016,10,18]],"date-time":"2016-10-18T07:24:17Z","timestamp":1476775457000},"page":"171-179","source":"Crossref","is-referenced-by-count":11,"title":["How to improve information extraction from German medical records"],"prefix":"10.1515","volume":"59","author":[{"given":"Johannes","family":"Starlinger","sequence":"first","affiliation":[{"name":"Humboldt-Universit\u00e4t zu Berlin, Institut f\u00fcr Informatik, Unter den Linden 6, 10099 Berlin Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Madeleine","family":"Kittner","sequence":"additional","affiliation":[{"name":"Humboldt-Universit\u00e4t zu Berlin, Institut f\u00fcr Informatik, Unter den Linden 6, 10099 Berlin Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oliver","family":"Blankenstein","sequence":"additional","affiliation":[{"name":"Charit\u00e9 Universit\u00e4tsmedizin Berlin, P\u00e4diatrische Endokrinologie und Diabetologie, Augustenburger Platz 1, 13353 Berlin Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ulf","family":"Leser","sequence":"additional","affiliation":[{"name":"Humboldt-Universit\u00e4t zu Berlin, Institut f\u00fcr Informatik, Unter den Linden 6, 10099 Berlin Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2016,10,19]]},"reference":[{"key":"ref31","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1016\/j.ajhg.2008.09.017","article-title":"The human phenotype ontology : a tool for anno - tating and analyzing human hereditary disease The American","volume":"40","author":"Robinson","year":"2008","journal-title":"Journal of Human Genetics"},{"key":"ref111","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1136\/jamia.2010.004119","article-title":"and Improving textual medication extraction using combined conditional random fields and rule - based sys - tems Journal of the","volume":"48","author":"Tikk","year":"2010","journal-title":"American Medical Informatics Association"},{"key":"ref131","first-page":"519","article-title":"Community annotation experiment for ground truth generation for the i medica - tion challenge Journal of the American Medical Informatics","volume":"50","author":"Uzuner","year":"2010","journal-title":"Association"},{"key":"ref61","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1136\/jamia.2009.001560","article-title":"Kipper Mayo clinical text analysis and knowledge extraction system cTAKES architecture com - ponent evaluation and applications Journal of the American","volume":"43","author":"Savova","year":"2010","journal-title":"Medical Informatics Association"},{"key":"ref141","first-page":"552","article-title":"i VA challenge on concepts assertions and relations in clinical text Journal of the","volume":"51","author":"Uzuner","year":"2010","journal-title":"American Medical Informatics Association"}],"container-title":["it - Information Technology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.degruyter.com\/view\/j\/itit.2017.59.issue-4\/itit-2016-0027\/itit-2016-0027.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2016-0027\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2016-0027\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,23]],"date-time":"2021-06-23T11:44:36Z","timestamp":1624448676000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2016-0027\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,10,19]]},"references-count":5,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2017,8,1]]},"published-print":{"date-parts":[[2017,8,28]]}},"alternative-id":["10.1515\/itit-2016-0027"],"URL":"https:\/\/doi.org\/10.1515\/itit-2016-0027","relation":{},"ISSN":["2196-7032","1611-2776"],"issn-type":[{"value":"2196-7032","type":"electronic"},{"value":"1611-2776","type":"print"}],"subject":[],"published":{"date-parts":[[2016,10,19]]}}}