R. Artstein and M. Poesio, Inter-Coder Agreement for Computational Linguistics, Computational Linguistics, vol.27, issue.1, 2008.
DOI : 10.1037/0033-2909.103.3.374
URL : http://doi.org/10.1162/coli.07-034-r2

E. Bigeard, V. Jouhet, F. Mougin, F. Thiessard, and N. Grabar, Automatic extraction of numerical values from unstructured data in EHRs, In: MIE (Medical Informatics in Europe, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01484996

B. Campillo-gimenez, C. Buscail, O. Zekri, B. Laguerre, L. Prisé et al., Improving the pre-screening of eligible patients in order to increase enrollment in cancer clinical trials, Trials, vol.20, issue.Suppl 1, pp.1-15, 2015.
DOI : 10.1007/978-3-642-17749-1_3
URL : https://hal.archives-ouvertes.fr/inserm-01111418

C. Watch, State of the clinical trials industry: A sourcebook of charts and statistics, Tech. rep., Center Watch, 2013.

D. Davidov and A. Rappaport, Extraction and approximation of numerical attributes from the web, 48th Annual Meeting of the Association for Computational Linguistics, pp.1308-1317, 2010.

B. Fletcher, A. Gheorghe, D. Moore, S. Wilson, and S. Damery, Improving the recruitment activity of clinicians in randomised controlled trials: a systematic review, BMJ Open, vol.2, issue.1, pp.1-14, 2012.
DOI : 10.1136/bmjopen-2011-000496

J. Lafferty, A. Mccallum, and F. Pereira, Conditional random fields: Probabilistic models for segmenting and labeling sequence data, International Conference on Machine Learning (ICML), 2001.

A. Madaan, A. Mitta, . Mausam, G. Ramakrishnan, and S. Sarawagi, Numerical relation extraction with minimal supervision, Thirtieth AAAI Conference on Artificial Intelligence, 2016.

C. Nath, M. Albaghdadi, and S. Jonnalagadda, A Natural Language Processing Tool for Large-Scale Data Extraction from Echocardiography Reports, PLOS ONE, vol.13, issue.4, pp.153749-64, 2016.
DOI : 10.1371/journal.pone.0153749.s003
URL : https://doi.org/10.1371/journal.pone.0153749

B. Olasov and I. Sim, Ruleed, a web-based semantic network interface for constructing and revising computable eligibility rules, AMIA Symposium. p, p.1051, 2006.

A. Pranjal, R. Delip, and R. Balaraman, Part Of speech Tagging and Chunking with HMM and CRF, Proceedings of NLP Association of India (NLPAI) Machine Learning Contest, 2006.

R. , S. P. Mandhan, S. Niwa, and Y. , Numerical atrribute extraction from clinical texts, 2016.

C. Raymond and J. Fayolle, Reconnaissance robuste d'entités nommées sur de la parole transcrite automatiquement, Actes de la conférence Traitement Automatique des Langues Naturelles, 2010.

H. Schmid, Probabilistic part-of-speech tagging using decision trees, Proc of International Conference on New Methods in Language Processing, pp.44-49, 1994.

F. Sebastiani, Machine learning in automated text categorization, ACM Computing Surveys, vol.34, issue.1, pp.1-47, 2002.
DOI : 10.1145/505282.505283

C. Shivade, P. Raghavan, E. Fosler-lussier, P. Embi, N. Elhadad et al., A review of approaches to identifying patient phenotype cohorts using electronic health records, Journal of the American Medical Informatics Association, vol.21, issue.2, pp.221-251, 2014.
DOI : 10.1136/amiajnl-2013-001935

T. Wang, J. Li, Q. Diao, W. Hu, Y. Z. Dulong et al., Semantic event detection using conditional random fields, IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW '06), 2006.