Patient Identification for Clinical Trials with Ontology-based Information Extraction from Documents

Peter Geibel, Hebun Erdur, Lothar Zimmermann, Stefan Krüger, Kati Jegzentis, Josef Schepers, Anne Becker, Frank Müller, Christian Hans Nolte, Jan Friedrich Scheitz, Serdar Tütüncü, Tatiana Usnich, Markus Frick, Martin Trautwein, Thorsten Schaaf, Alfred Holzgreve, Thomas Tolxdorff

Abstract

In this paper, we describe the use of ontologies in the context of a system for recruiting patients for clinical trials, which is currently being tested at the {\em Charit\'{e} – Universitätsmedizin Berlin}, one of the largest university hospitals in Europe. The main purpose of the CRDW (Clinical Research Data Warehouse) is to support patient recruitment for clinical trials based on routine data from the hospital's clinical information system (CIS). In contrast to most other systems for similar purposes, the CRDW also makes use of information that is present in clinical documents like admission reports, radiological findings, and discharge letters. The linguistic analysis recognizes negated and coordinated phrases. It is supported by clinical domain ontologies that enable the identification of main terms and their properties, as well as semantic search with synonyms, hypernyms, and syntactic variants. The focus of this paper is the description of our ontology model, which we tailored to the particular requirements of our application. In the article, we will also provide an evaluation of the system based on experimental data obtained from the daily routine work of the study assistants.

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Paper Citation


in Harvard Style

Geibel P., Erdur H., Zimmermann L., Krüger S., Jegzentis K., Schepers J., Becker A., Müller F., Nolte C., Scheitz J., Tütüncü S., Usnich T., Frick M., Trautwein M., Schaaf T., Holzgreve A. and Tolxdorff T. (2013). Patient Identification for Clinical Trials with Ontology-based Information Extraction from Documents . In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013) ISBN 978-989-8565-81-5, pages 230-236. DOI: 10.5220/0004544702300236


in Bibtex Style

@conference{keod13,
author={Peter Geibel and Hebun Erdur and Lothar Zimmermann and Stefan Krüger and Kati Jegzentis and Josef Schepers and Anne Becker and Frank Müller and Christian Hans Nolte and Jan Friedrich Scheitz and Serdar Tütüncü and Tatiana Usnich and Markus Frick and Martin Trautwein and Thorsten Schaaf and Alfred Holzgreve and Thomas Tolxdorff},
title={Patient Identification for Clinical Trials with Ontology-based Information Extraction from Documents},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013)},
year={2013},
pages={230-236},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004544702300236},
isbn={978-989-8565-81-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013)
TI - Patient Identification for Clinical Trials with Ontology-based Information Extraction from Documents
SN - 978-989-8565-81-5
AU - Geibel P.
AU - Erdur H.
AU - Zimmermann L.
AU - Krüger S.
AU - Jegzentis K.
AU - Schepers J.
AU - Becker A.
AU - Müller F.
AU - Nolte C.
AU - Scheitz J.
AU - Tütüncü S.
AU - Usnich T.
AU - Frick M.
AU - Trautwein M.
AU - Schaaf T.
AU - Holzgreve A.
AU - Tolxdorff T.
PY - 2013
SP - 230
EP - 236
DO - 10.5220/0004544702300236