P. Lependu, S. Iyer, A. Bauer-mehren, R. Harpaz, J. Mortensen et al., Pharmacovigilance Using Clinical Notes, Clinical Pharmacology & Therapeutics, vol.14, issue.4, pp.547-55, 2013.
DOI : 10.1016/j.websem.2012.02.003

T. Sakaeda, A. Tamon, K. Kadoyama, and Y. Okuno, Data Mining of the Public Version of the FDA Adverse Event Reporting System, International Journal of Medical Sciences, vol.10, issue.7, pp.796-803, 2013.
DOI : 10.7150/ijms.6048

E. Roitmann, R. Eriksson, and S. Brunak, Patient stratification and identification of adverse event correlations in the space of 1190 drug related adverse events, Frontiers in Physiology, vol.106, p.332, 2014.
DOI : 10.1073/pnas.0808904106

R. Winnenburg, A. Sorbello, and O. Bodenreider, Exploring adverse drug events at the class level, Journal of Biomedical Semantics, vol.93, issue.1, p.18, 2015.
DOI : 10.1038/clpt.2013.24

B. Ganter and R. Wille, Formal Concept Analysis: Mathematical Foundations, 1997.

B. Ganter and S. Kuznetsov, Pattern Structures and Their Projections, Proceedings of the International Conference on Conceptual Structures (ICCS), pp.129-171, 2001.
DOI : 10.1007/3-540-44583-8_10

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.7648

A. Lillo-le-louët, Y. Toussaint, and J. Villerd, A qualitative approach to signal mining in pharmacovigilance using formal concept analysis. Stud Health Tech Inf, pp.969-73, 2009.

J. Villerd, Y. Toussaint, L. Louët, and A. , Adverse Drug Reaction Mining in Pharmacovigilance Data Using Formal Concept Analysis, Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp.386-401, 2010.
DOI : 10.1007/978-3-642-15939-8_25

URL : https://hal.archives-ouvertes.fr/inria-00599549

A. Vasudevan and E. Ginzler, Established and novel treatments for lupus: agents in clinical trials are targeting various immunological processes, J Musculoskelet Med, vol.26, issue.8, pp.291-292, 2009.

J. Banda, L. Evans, R. Vanguri, N. Tatonetti, P. Ryan et al., A curated and standardized adverse drug event resource to accelerate drug safety research. Sci data, 2016.
DOI : 10.1038/sdata.2016.26

URL : http://doi.org/10.1038/sdata.2016.26

H. Lowe, T. Ferris, P. Hernandez, and S. Weber, STRIDE-an integrated standards-based translational research informatics platform, AMIA Annual Symposium Proceedings. AMIA, p.391, 2009.

M. Kuhn, I. Letunic, L. Jensen, and P. Bork, The SIDER database of drugs and side effects, Nucleic Acids Research, vol.44, issue.D1, 2015.
DOI : 10.1093/nar/gkv1075

T. Kakar, X. Qin, S. Wunnava, and E. Rundensteiner, Towards pharmacovigilance using machine learning to identify unknown adverse reactions triggered by drug-drug interaction, Poster abstracts of the Annual Research Retreat of the UMass Center for Clinical and Translational Science, 2016.

R. Agrawal, T. Imielí-nski, and A. Swami, Mining association rules between sets of items in large databases, Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data

R. Agrawal and R. Srikant, Fast algorithms for mining association rules, Proc. 20th Int. Conf. Very Large Data Bases, VLDB, pp.487-99, 1994.

N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal, Efficient mining of association rules using closed itemset lattices, Information Systems, vol.24, issue.1, pp.25-46, 1999.
DOI : 10.1016/S0306-4379(99)00003-4

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.23.2928

L. Lakhal and G. Stumme, Efficient Mining of Association Rules Based on Formal Concept Analysis, Lecture Notes in Computer Science, vol.3626, pp.180-95, 2005.
DOI : 10.1007/11528784_10

M. Kaytoue, V. Codocedo, A. Buzmakov, J. Baixeries, S. Kuznetsov et al., Pattern Structures and Concept Lattices for Data Mining and Knowledge Processing, Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp.227-258, 2015.
DOI : 10.1007/978-3-319-23461-8_19

URL : https://hal.archives-ouvertes.fr/hal-01188637

A. Coulet, F. Domenach, M. Kaytoue, and A. Napoli, Using Pattern Structures for Analyzing Ontology-Based Annotations of Biomedical Data, Proceedings of the International Conference on Formal Concept Analysis, pp.76-91, 2013.
DOI : 10.1007/978-3-642-38317-5_5

URL : https://hal.archives-ouvertes.fr/hal-00922392

R. Harpaz, W. Dumouchel, P. Lependu, A. Bauer-mehren, P. Ryan et al., Performance of Pharmacovigilance Signal-Detection Algorithms for the FDA Adverse Event Reporting System, Clinical Pharmacology & Therapeutics, vol.44, issue.6, pp.539-585, 2013.
DOI : 10.2307/2531595