Znaidi, Eya and Tamine, Lynda and Latiri, Chiraz Answering PICO Clinical Questions: a Semantic Graph-Based Approach. (2015) In: 15th Conference on Artificial Intelligence in Medicine (AIME 15), 17 June 2015 - 20 June 2015 (Pavia, Italy).
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(Document in English)
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Official URL: http://dx.doi.org/10.1007/978-3-319-19551-3_30
Abstract
In this paper, we tackle the issue related to the retrieval of the best evidence that fits with a PICO (Population, Intervention, Comparison and Outcome) question. We propose a new document ranking algorithm that relies on semantic based query expansion bounded by the local search context to better discard irrelevant documents. Experiments using a standard dataset including 423 PICO questions and more than 1,2 million of documents, show that our aproach is promising.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Thanks to Springer editor. This papers appears in Volume 9105 Lecture Notes in Computer Science ISSN : 0302-9743. ISBN: 978-3-319-19550-6. The original PDF is available at : http://link.springer.com/chapter/10.1007%2F978-3-319-19551-3_30 |
HAL Id: | hal-01363309 |
Audience (conference): | International conference proceedings |
Uncontrolled Keywords: | |
Institution: | French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE) Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE) Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE) Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE) Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE) Other partners > Université de Tunis - El Manar (TUNISIA) |
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Deposited On: | 29 Aug 2016 14:12 |
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