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000144793 037__ $$aDKFZ-2019-02225
000144793 041__ $$aeng
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000144793 1001_ $$aMate, Sebastian$$b0
000144793 245__ $$aPan-European Data Harmonization for Biobanks in ADOPT BBMRI-ERIC.
000144793 260__ $$aStuttgart$$bSchattauer$$c2019
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000144793 520__ $$aHigh-quality clinical data and biological specimens are key for medical research and personalized medicine. The Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium (BBMRI-ERIC) aims to facilitate access to such biological resources. The accompanying ADOPT BBMRI-ERIC project kick-started BBMRI-ERIC by collecting colorectal cancer data from European biobanks. To transform these data into a common representation, a uniform approach for data integration and harmonization had to be developed. This article describes the design and the implementation of a toolset for this task. Based on the semantics of a metadata repository, we developed a lexical bag-of-words matcher, capable of semiautomatically mapping local biobank terms to the central ADOPT BBMRI-ERIC terminology. Its algorithm supports fuzzy matching, utilization of synonyms, and sentiment tagging. To process the anonymized instance data based on these mappings, we also developed a data transformation application. The implementation was used to process the data from 10 European biobanks. The lexical matcher automatically and correctly mapped 78.48% of the 1,492 local biobank terms, and human experts were able to complete the remaining mappings. We used the expert-curated mappings to successfully process 147,608 data records from 3,415 patients. A generic harmonization approach was created and successfully used for cross-institutional data harmonization across 10 European biobanks. The software tools were made available as open source.
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000144793 7001_ $$aKampf, Marvin$$b1
000144793 7001_ $$aRödle, Wolfgang$$b2
000144793 7001_ $$aKraus, Stefan$$b3
000144793 7001_ $$0P:(DE-He78)c0313b77e0c44cd2f5eb85b747c88be0$$aProynova, Rumyana$$b4$$udkfz
000144793 7001_ $$aSilander, Kaisa$$b5
000144793 7001_ $$0P:(DE-HGF)0$$aEbert, Lars$$b6
000144793 7001_ $$0P:(DE-He78)e4ad7b4e684492de43cfcb12e5397439$$aLablans, Martin$$b7$$udkfz
000144793 7001_ $$aSchüttler, Christina$$b8
000144793 7001_ $$aKnell, Christian$$b9
000144793 7001_ $$aEklund, Niina$$b10
000144793 7001_ $$aHummel, Michael$$b11
000144793 7001_ $$aHolub, Petr$$b12
000144793 7001_ $$aProkosch, Hans-Ulrich$$b13
000144793 773__ $$0PERI:(DE-600)2540042-3$$a10.1055/s-0039-1695793$$gVol. 10, no. 4, p. 679 - 692$$n4$$p679 - 692$$tApplied clinical informatics$$v10$$x1869-0327$$y2019
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