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Answering PICO Clinical Questions: a Semantic Graph-Based Approach

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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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)
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 - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (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 By: IRIT IRIT
Deposited On:29 Aug 2016 14:12

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