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Cloud-gebaseerde zin Mining en analyse van User-Defined Phrase-categorie vereniging in biomedische publicaties
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Cloud-gebaseerde zin Mining en analyse van User-Defined Phrase-categorie vereniging in biomedische publicaties

Article DOI: 10.3791/59108-v • 09:20 min • February 23rd, 2019
February 23rd, 2019 •
*1,2, *1,2, *1, 3, 1,2,4, 5, 5, 5, 1,6,7, 5, 1,2,4,6
1The NIH BD2K Center of Excellence in Biomedical Computing, University of California, Los Angeles, 2Department of Physiology, University of California, Los Angeles, 3Department of Pediatric and Adult Congenital Heart Surgery, Miller Children's and Women's Hospital and Long Beach Memorial Hospital, 4Department of Medicine/Cardiology, University of California, Los Angeles, 5NIH BD2K Program Centers of Excellence for Big Data Computing -- KnowEng Center, Department of Computer Science, University of Illinois at Urbana-Champaign (UIUC), 6Scalable Analytics Institute (ScAi), University of California, Los Angeles, 7Department of Computer Science, University of California, Los Angeles
* These authors contributed equally

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We presenteren een protocol en de bijbehorende programmacode evenals metagegevens monsters ter ondersteuning van een cloud-gebaseerde automatische identificatie van zinnen-categorie vereniging van unieke concepten in het domein van de geselecteerde kennis van de gebruiker in de biomedische literatuur. De vereniging van de zin-categorie gekwantificeerd door dit protocol kan vergemakkelijken diepgaande analyse in het domein van de geselecteerde kennis.

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Geneeskunde kwestie 144 text-mining gegevens wetenschap medische informatica zin mijnbouw cloud computing
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