Publications

36 Publications visible to you, out of a total of 36

Abstract

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Authors: Alfred Winter, Sebastian Stäubert, Danny Ammon, Stephan Aiche, Oya Beyan, Verena Bischoff, Philipp Daumke, Stefan Decker, Gert Funkat, Jan Erik Gewehr, Armin de Greiff, Silke Haferkamp, Udo Hahn, Andreas Henkel, Toralf Kirsten, Thomas Klöss, Jörg Lippert, Matthias Löbe, Volker Lowitsch, Oliver Maassen, Jens Maschmann, Sven Meister, Rafael Mikolajczyk, Matthias Nüchter, Mathias W. Pletz, Erhard Rahm, Morris Riedel, Kutaiba Saleh, Andreas Schuppert, Stefan Smers, André Stollenwerk, Stefan Uhlig, Thomas Wendt, Sven Zenker, Wolfgang Fleig, Gernot Marx, André Scherag, Markus Löffler

Date Published: 2018

Publication Type: Journal article

Abstract (Expand)

BACKGROUND Medical plaintext documents contain important facts about patients, but they are rarely available for structured queries. The provision of structured information from natural language textss in addition to the existing structured data can significantly speed up the search for fulfilled inclusion criteria and thus improve the recruitment rate. OBJECTIVES This work is aimed at supporting clinical trial recruitment with text mining techniques to identify suitable subjects in hospitals. METHOD Based on the inclusion/exclusion criteria of 5 sample studies and a text corpus consisting of 212 doctor’s letters and medical follow-up documentation from a university cancer center, a prototype was developed and technically evaluated using NLP procedures (UIMA) for the extraction of facts from medical free texts. RESULTS It was found that although the extracted entities are not always correct (precision between 23% and 96%), they provide a decisive indication as to which patient file should be read preferentially. CONCLUSION The prototype presented here demonstrates the technical feasibility. In order to find available, lucrative phenotypes, an in-depth evaluation is required.

Authors: Matthias Löbe, Sebastian Stäubert, Colleen Goldberg, Ivonne Haffner, Alfred Winter

Date Published: 2018

Publication Type: Journal article

Abstract (Expand)

The SNIK project converts textbooks about information management in hospitals to a domain ontology that provides a shared vocabulary for institutions to model and integrate processes, data and infrastructure. To accommodate user groups with different requirements and technical backgrounds, and to support incremental and cooperative development, we create a system architecture to publish, visualize, browse and query the ontology, as well as to evaluate and improve the data quality.

Authors: Konrad Höffner, Franziska Jahn, Christian Kücherer, Barbara Paech, Birgit Schneider, Martin Schöbel, Sebastian Stäubert, Alfred Winter

Date Published: 2017

Publication Type: InCollection

Abstract

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Authors: Martin Schöbel, Sebastian Stäubert, Matthias Löbe, Kirsti Meinel, Alfred Winter

Date Published: 2016

Publication Type: InProceedings

Abstract

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Authors: Sebastian Stäubert, Ulrike Weber, C. Michalik, J. Dress, Sylvie M. N. Ngouongo, Jürgen Stausberg, Alfred Winter

Date Published: 2016

Publication Type: InProceedings

Abstract

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Authors: Karsten Brandt, Matthias Löbe, Michael Schaaf, Franziska Jahn, Alfred Winter, Sebastian Stäubert

Date Published: 2016

Publication Type: InProceedings

Abstract

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Authors: Sebastian Stäubert, Kirsti Meinel, Frank Meineke, Matthias Löbe, Alfred Winter

Date Published: 2015

Publication Type: InProceedings

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