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Medical Entity Corpus with PICO Elements and Sentiment Analysis
TU Wien, Vienna, Austria..
TU Wien, Vienna, Austria..
TU Wien, Vienna, Austria..
Stockholm Univ, Stockholm, Sweden..
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2018 (English)In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) / [ed] Nicoletta Calzolari, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Koiti Hasida, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis & Takenobu Tokunaga, 2018, p. 292-296Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present our process to establish a PICO and a sentiment annotated corpus of clinical trial publications. PICO stands for Population, Intervention, Comparison and Outcome - these four classes can be used for more advanced and specific search queries. For example, a physician can determine how well a drug works only in the subgroup of children. Additionally to the PICO extraction, we conducted a sentiment annotation, where the sentiment refers to whether the conclusion of a trial was positive, negative or neutral. We created both corpora with the help of medical experts and non-experts as annotators.

Place, publisher, year, edition, pages
2018. p. 292-296
Keywords [en]
sentiment analysis, PICO, medical corpus, annotation
National Category
Natural Language Processing
Identifiers
URN: urn:nbn:se:uu:diva-476878ISI: 000725545000044ISBN: 979-10-95546-00-9 (print)OAI: oai:DiVA.org:uu-476878DiVA, id: diva2:1670630
Conference
11th International Conference on Language Resources and Evaluation (LREC), MAY 07-12, 2018, Miyazaki, JAPAN
Funder
EU, Horizon 2020, 644753Available from: 2022-06-16 Created: 2022-06-16 Last updated: 2025-02-07Bibliographically approved

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Citation style
  • apa
  • ieee
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Language
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  • nn-NO
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Output format
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