Mining Association Rules between Sets of Items in Large Databases, Proceedings of the ACM SIGMOD International Conference on Management of Data, 1993. ,
Fast algorithms for mining association rules in large databases, Proceedings of the 20th International Conference on Very Large Data Bases, VLDB, pp.487-499, 1994. ,
Perspectives on the Use of Data Mining in Pharmacovigilance, Drug Safety, vol.12, issue.6, pp.981-1007, 2005. ,
DOI : 10.2165/00002018-200528110-00002
Novel Statistical Tools for Monitoring the Safety of Marketed Drugs, Clinical Pharmacology & Therapeutics, vol.15, issue.2, pp.157-66, 2007. ,
DOI : 10.1038/sj.clpt.6100258
Typologie et méthode d'évaluation des systèmes de signalement des accidents médicaux et des événements indésirables Advanced Econometrics, Report, 1985. ,
Extraction of adverse drug effects from clinical records, Stud Health Technol Inform, vol.160, pp.739-782, 2010. ,
Drug therapy Davidson's principles and practice of medicine 19th ed Anatomical and Therapeutical Classification, p.147, 2002. ,
The Expert Explorer: A Tool for Hospital Data Visualization and Adverse Event Rules Validation, Studies in Health Technology and Informatics, vol.148, pp.85-94, 2009. ,
Handbook of the Logistic Distribution, 1991. ,
Latent Variable Models and Factor Analysis, 1999. ,
DOI : 10.1002/9781119970583
Data Mining in Spontaneous Reports, Basic <html_ent glyph="@amp;" ascii="&"/> Clinical Pharmacology <html_ent glyph="@amp;" ascii="&"/> Toxicology, vol.2663, issue.3, pp.324-354, 2006. ,
DOI : 10.1002/pds.668
Potential Identifiability and Preventability of Adverse Events Using Information Systems, Journal of the American Medical Informatics Association, vol.1, issue.5, pp.404-415, 1994. ,
DOI : 10.1136/jamia.1994.95153428
Incidence of adverse drug events and potential adverse drug events. Implications for prevention. ADE Prevention Study Group, JAMA: The Journal of the American Medical Association, vol.274, issue.1, pp.29-34, 1995. ,
DOI : 10.1001/jama.274.1.29
Detecting Adverse Events Using Information Technology, Journal of the American Medical Informatics Association, vol.10, issue.2, pp.115-143, 1997. ,
DOI : 10.1197/jamia.M1074
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC150365
Evaluation of Serious Adverse Drug Reactions, Archives of Internal Medicine, vol.167, issue.10, pp.1041-1050, 2007. ,
DOI : 10.1001/archinte.167.10.1041
Comparison of manual and automated documentation of adverse events with an Anesthesia Information Management System (AIMS), Stud Health Technol Inform, vol.77, pp.925-934, 2000. ,
Analyse de Données : la Taxinomie, 1973. ,
Adverse Event Detection in Drug Development: Recommendations and Obligations Beyond Phase 3, American Journal of Public Health, vol.98, issue.8, 2008. ,
DOI : 10.2105/AJPH.2007.124537
Dynamic itemset counting and implication rules for market basket data, Proceedings ACM SIGMOD International Conference on Management of Data, pp.255-264, 1997. ,
Available from: http//sqlpro.developpez.com/cours/soundex Using trigger phrases to detect adverse drug reactions in ambulatory care notes. Qual Saf Health Care, pp.132-136, 2007. ,
Application of Data Mining for Examining Polypharmacy and Adverse Effects in Cardiology Patients, Cardiovascular Toxicology, vol.1, issue.3, pp.177-186, 2001. ,
DOI : 10.1385/CT:1:3:177
Detection of adverse drug events: proposal of a data model, Stud Health Technol Inform, vol.148, issue.1, pp.63-74, 2009. ,
Data-mining-based detection of adverse drug events Detection of adverse drug events detection: data aggregation and data mining, Stud Health Technol Inform. Stud Health Technol Inform, vol.150148, issue.23, pp.552-675, 2009. ,
Adverse drug events prevention rules: multi-site evaluation of rules from various sources, Stud Health Technol Inform, vol.148, issue.4, pp.102-113, 2009. ,
Adverse drug events in hospitalized patients. Excess length of stay, extra costs, and attributable mortality Computerized surveillance of adverse drug events in hospital patients Qual Saf Health Care, JAMA, 1991. ,
Further Normalization of the Data Base Relational Model Data Base Systems: Courant Computer Science Symposia Series 6 The Relational Model for Database Management: Version 2, IBM Research Report RJ909. Republished in, 1972. ,
Apprentissage artificiel concepts et algorithmes. Eyrolles, 2001. ,
Antipsychotic drugs and heart muscle disorder in international pharmacovigilance: data mining study, BMJ, vol.322, issue.7296, pp.1207-1216, 2001. ,
DOI : 10.1136/bmj.322.7296.1207
Regression Models and Life-Tables, Journal of the Royal Statistical Society Series B, vol.34, issue.2, pp.187-220, 1972. ,
DOI : 10.1007/978-1-4612-4380-9_37
An Introduction to Database Systems, 1999. ,
Database in Depth: Relational Theory for Practitioners, 2005. ,
Expected Behaviour of Quartet Distances Between Undirected Phylogenetic Trees, Eightennth International Numerical Taxonomy Conference, pp.5-8, 1984. ,
Comparison of two knowledge bases on the detection of drug-drug interactions, Proc AMIA Symp, pp.171-176, 2000. ,
Optimisation en Classification Automatique, tomes 1 et 2. INRIA On the optimality of the simple Bayesian classifier under zero-one loss, Domingos P, Pazzani M Machine Learning, vol.29, pp.103-137, 1980. ,
Rule induction and instance-based learning applied in medical diagnosis. Technol Health Care, pp.203-224, 1996. ,
EC on the Community code relating to medicinal products for human use Available from: http://eurlex .europa.eu/LexUriServ/LexUriServ.do?uri=CONSLEG, CampbellEM. Automating Concept Identification in the Electronic Medical Record: An Experiment in Extracting Dosage Information. AMIA 1996 Symposium Proceedings, pp.388-92, 1996. ,
An Introduction to Latent Variable Models From data mining to knowledge discovery: an overview. 2nd Int Conf on Knowledge Discovery and Data Mining; 1996. [FDA 2010] MedWatch -What Is A Serious Adverse Event? [cited Strategies for detecting adverse drug events among older persons in the ambulatory setting, October J Am Med Inform Assoc, issue.6, pp.11-492, 1984. ,
Outpatient prescribing errors and the impact of computerized prescribing, Journal of General Internal Medicine, vol.8, issue.suppl 4, pp.837-878, 2005. ,
DOI : 10.1111/j.1525-1497.2005.0194.x
Fast k nearest neighbor search using GPU Incidence and preventability of adverse drug events in nursing homes, Extracting Structured Medication Event Information from Discharge Summaries AMIA 2008 Symposium Proceedings 237-241, pp.87-94, 2000. ,
Incidence and Preventability of Adverse Drug Events Among Older Persons in the Ambulatory Setting, JAMA, vol.289, issue.9, pp.1107-1123, 2003. ,
DOI : 10.1001/jama.289.9.1107
Natural language processing to identify adverse drug events Applied latent class analysis, AMIA Annu Symp Proc. 2008:961, 2002. ,
Idiot's Bayes -not so stupid after all? Epidemiology of medicationrelated adverse events in nursing homes A systematic review of the performance characteristics of clinical event monitor signals used to detect adverse drug events in the hospital setting, International Statistical Review. Am J Ger Pharma J Am Med Inform Assoc, vol.6914, issue.34, pp.385-399451, 2001. ,
New probabilistic interest measures for association rules. Intelligent Data Analysis, pp.437-455, 2007. ,
Data Mining in Pharmacovigilance, Drug Safety, vol.12, issue.6, pp.835-877, 2005. ,
DOI : 10.2165/00002018-200528100-00001
Using Computerized Data to Identify Adverse Drug Events in Outpatients, Journal of the American Medical Informatics Association, vol.8, issue.3, pp.254-66, 2001. ,
DOI : 10.1136/jamia.2001.0080254
A computerized method for identifying incidents associated with adverse drug events in outpatients, International Journal of Medical Informatics, vol.61, issue.1, pp.21-32, 2001. ,
DOI : 10.1016/S1386-5056(00)00131-3
Risk factors for nephrotoxicity associated with continuous vancomycin infusion in outpatient parenteral antibiotic therapy, Journal of Antimicrobial Chemotherapy, vol.62, issue.1, pp.168-71, 2008. ,
DOI : 10.1093/jac/dkn080
DC: The National Academic Press Human-centred design processes for interactive systems, Improving Computerized Provider Order Entry (CPOE) usability by data mining users' queries from access logs. AMIA Annu Symp Proc, pp.379-83, 1999. ,
Identifying Adverse Drug Events: Development of a Computer-based Monitor and Comparison with Chart Review and Stimulated Voluntary Report, Journal of the American Medical Informatics Association, vol.5, issue.3, pp.305-319, 1998. ,
DOI : 10.1136/jamia.1998.0050305
Can Surveillance Systems Identify and Avert Adverse Drug Events? A Prospective Evaluation of a Commercial Application, Journal of the American Medical Informatics Association, vol.15, issue.5, pp.647-53, 2006. ,
DOI : 10.1197/jamia.M2634
Prescribers' Responses to Alerts During Medication Ordering in the Long Term Care Setting, Journal of the American Medical Informatics Association, vol.13, issue.4, pp.385-90, 2006. ,
DOI : 10.1197/jamia.M1945
Effects of Computerized Physician Order Entry and Clinical Decision Support Systems on Medication Safety, Archives of Internal Medicine, vol.163, issue.12, pp.1409-1425, 2003. ,
DOI : 10.1001/archinte.163.12.1409
Automated Surveillance for Adverse Drug Events at a Community Hospital and an Academic Medical Center, Journal of the American Medical Informatics Association, vol.13, issue.4, pp.372-379, 2006. ,
DOI : 10.1197/jamia.M2069
To Err Is Human: Building a Safer Health System National Academy Pr Increasing the Classification Accuracy of Simple Bayesian Classifier A new knowledge structure for drug-drug interactions, Lecture Notes in Artificial Intelligence Proc Annu Symp Comput Appl Med Care, vol.3192, pp.198-207, 1994. ,
Detecting alerts, notifying the physician, and offering action items: a comprehensive alerting system, Proc AMIA Annu Fall Symp, pp.704-712, 1996. ,
Improving Response to Critical Laboratory Results with Automation: Results of a Randomized Controlled Trial, Journal of the American Medical Informatics Association, vol.6, issue.6, pp.512-534, 1999. ,
DOI : 10.1136/jamia.1999.0060512
Selected techniques for data mining in medicine, Artificial Intelligence in Medicine, vol.16, issue.1, 1999. ,
DOI : 10.1016/S0933-3657(98)00062-1
Latent Structure Analysis, Houghton Mifflin, 1968. ,
Some Methods for classification and Analysis of Multivariate Observations Generalized Linear Models, Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, pp.281-297, 1967. ,
Latent Class Analysis Makhoul, John; Francis Kubala; Richard Schwartz; Ralph Weischedel: Performance measures for information extraction, Proceedings of DARPA Broadcast News Workshop, 1987. ,
Automated Detection of Adverse Events Using Natural Language Processing of Discharge Summaries, Journal of the American Medical Informatics Association, vol.12, issue.4, pp.448-57, 2005. ,
DOI : 10.1197/jamia.M1794
Steps toward Artificial Intelligence, Proceedings of the IRE, vol.49, issue.1, pp.8-30, 1961. ,
DOI : 10.1109/JRPROC.1961.287775
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.79.7413
Adverse drug events and medication errors: detection and classification methods. Qual Saf Health Care, pp.306-320, 2004. ,
Nomograms for Visualization of Naive Bayesian Classifier, Proc. of PKDD-2004, pp.337-348, 2004. ,
Detecting adverse events for patient safety research: a review of current methodologies, Journal of Biomedical Informatics, vol.36, issue.1-2, pp.131-174, 2003. ,
DOI : 10.1016/j.jbi.2003.08.003
Statistique explicative appliquée Approche pragmatique de la classification Evaluation and NLP. proceedings of DEXA Database and Expert System Application, Nakache J, pp.626-632, 2003. ,
High rates of adverse drug events in a highly computerized hospital Automatic indexing of online health resources for a French quality controlled gateway Information Processing & Management Evaluation of a Simple Method for the Automatic Assignment of MeSH Descriptors to Health Resources in a French Online Catalogue, Arch Int Med Stud Health Technol Inform, vol.42, issue.3, pp.695-709, 2005. ,
Using multi-terminology indexing for the assignment of MeSH descriptors to health resources in a French online catalogue. AMIA symp Multi-terminology indexing for the assignment of MeSH descriptors to medical abstracts in French, AMIA2009, Biomedical and Health Informatics: From foundations to Applications to policy, pp.586-590, 2008. ,
URL : https://hal.archives-ouvertes.fr/hal-00503262
Potentially preventable adverse events identified by physician self-report and medical record review: demographic and resource utilization data Knowledge discovery in databases [PSIP 2010] Patient Safety by Intelligent Procedures in medication, Clin Res. Pharmacorama, vol.40, 1991. ,
Introduction of Decision Trees, Machine Learning, vol.1, pp.81-106, 1986. ,
C4.5 : Programs for Machine Learning R_Development_Core_Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing Graphes d'induction Arbre de décision, Revue Modulad, vol.33, pp.163-187, 1993. ,
Pathogenesis of adverse drug reactions Textbook of adverse drug reactions, p.10, 1977. ,
An empirical study of the naive Bayes classifier What evidence supports the use of computerized alerts and prompts to improve clinicians' prescribing behavior? Adverse drug event detection in a community hospital utilising computerised medication and laboratory data, Rish I. IJCAI Workshop on Empirical Methods in Artificial Intelligence. J Am Med Inform Assoc Drug Saf, vol.1630, issue.49, pp.531-8817, 1996. ,
Practical approach to determining costs and frequency of adverse drug events in a health care network, Shakhnarovish 2005] Shakhnarovich G, Darrell T & Indyk P. Nearest-Neighbor Methods in Learning and Vision. Edited by Shakhnarovish, Darrell, and Indyk, 2001. ,
STUDY OF EFFECT OF DRUG LEXICONS ON MEDICATION EXTRACTION FROM ELECTRONIC MEDICAL RECORDS, Biocomputing 2005, pp.308-326, 2005. ,
DOI : 10.1142/9789812702456_0029
Grand challenges in clinical decision support, Journal of Biomedical Informatics, vol.41, issue.2, pp.387-92, 2008. ,
DOI : 10.1016/j.jbi.2007.09.003
Rpart: Recursive Partitioning [Tuyns 1988] Tuyns AJ et al. Cancer of the larynx/hypopharynx, tobacco and alcohol: IARC international case-control study in Turin and Varese (Italy) Geneva (Switzerland) and Calvados (France). 1988. [Van Rijsbergen 1979] Van Rijsbergen Modern Applied Statistics with S, Zaragoza and Navarra (Spain) C.V.: Information Retrieval. London; Boston. Butterworth Venables WN & Ripley BD, 1979. ,
World Health Organization Adverse Reactions Terminology Available from: http://www.umc-products.com/DynPage.aspx?id=4918 World Organisation of National Colleges, Academies, and Academic Associations of General Practitioners/Family Physicians3)] World Health Organization. International Classification of Diseases, 10th revision, 2001. ,
Tree structural statistical methods. Encyclopedia of Biostatistics, pp.4561-73, 2001. ,
Can F-MTI semantic-mined drug codes be used for Adverse Drug Events detection when no CPOE is available?, Health Technol Inform, vol.160, pp.1025-1034, 2010. ,
Data-mining-based detection of adverse drug events, Stud Health Technol Inform, vol.150, pp.552-558, 2009. ,
Adverse drug events prevention rules: multi-site evaluation of rules from various sources, Beuscart R. Stud Health Technol Inform, vol.148, pp.102-113, 2009. ,
The expert explorer: a tool for hospital data visualization and adverse drug event rules validation, Stud Health Technol Inform, vol.148, pp.85-94, 2009. ,
Detection of adverse drug events detection: data aggregation and data mining, PSIP consortium, Beuscart R. Stud Health Technol Inform, vol.148, pp.75-84, 2009. ,
Detection of adverse drug events: proposal of a data model, Beuscart R. Stud Health Technol Inform, vol.148, pp.63-74, 2009. ,