Big data, but are we ready?, Nature Reviews Genetics, vol.11, issue.3, p.224, 2011. ,
DOI : 10.1038/nrg2857-c1
Translational research in infectious disease: current paradigms and challenges ahead, Translational Research, vol.159, issue.6, pp.430-453, 2012. ,
DOI : 10.1016/j.trsl.2011.12.009
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3361696
The coming age of data-driven medicine: translational bioinformatics' next frontier, Journal of the American Medical Informatics Association, vol.19, issue.e1, pp.2-4 ,
DOI : 10.1136/amiajnl-2012-000969
Causes of early-onset type 1 diabetes: toward data-driven environmental approaches, The Journal of Experimental Medicine, vol.131, issue.13, pp.2953-2957, 2008. ,
DOI : 10.1038/nature06014
When One and One Gives More than Two: Challenges and Opportunities of Integrative Omics, Frontiers in Genetics, vol.2, p.105, 2011. ,
DOI : 10.3389/fgene.2011.00105
The Inevitable Application of Big Data to Health Care, JAMA, vol.309, issue.13, pp.1351-1352 ,
DOI : 10.1001/jama.2013.393
A survey of variable selection methods in two Chinese epidemiology journals, BMC Medical Research Methodology, vol.57, issue.1, p.87, 2010. ,
DOI : 10.1016/j.jclinepi.2003.05.003
Variable selection: current practice in epidemiological studies, European Journal of Epidemiology, vol.55, issue.1, pp.733-736, 2009. ,
DOI : 10.1007/s10654-009-9411-2
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2791468
A simulation study of the number of events per variable in logistic regression analysis, Journal of Clinical Epidemiology, vol.49, issue.12, pp.1373-1379, 1996. ,
DOI : 10.1016/S0895-4356(96)00236-3
Data mining: data analysis on a grand scale?, Statistical Methods in Medical Research, vol.32, issue.4, pp.309-327, 2000. ,
DOI : 10.1177/096228020000900402
A comparison of regression trees, logistic regression, generalized additive models, and multivariate adaptive regression splines for predicting AMI mortality, Statistics in Medicine, vol.30, issue.15, pp.2937-2957, 2007. ,
DOI : 10.1002/sim.2770
Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests, BMC Research Notes, vol.4, issue.1, p.299, 2011. ,
DOI : 10.1016/0167-8655(95)00113-1
Comparison between neural networks and multiple logistic regression to predict acute coronary syndrome in the emergency room, Artificial Intelligence in Medicine, vol.38, issue.3, pp.305-318, 2006. ,
DOI : 10.1016/j.artmed.2006.07.006
Machine learning for improved pathological staging of prostate cancer: A performance comparison on a range of classifiers, Artificial Intelligence in Medicine, vol.55, issue.1, pp.25-35, 2012. ,
DOI : 10.1016/j.artmed.2011.11.003
Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble-based methods?, Biometrical Journal, vol.5, issue.5, pp.657-673 ,
DOI : 10.1002/bimj.201100251
Using methods from the data-mining and machine-learning literature for disease classification and prediction: a case study examining classification of heart failure subtypes, Journal of Clinical Epidemiology, vol.66, issue.4, pp.398-407, 2013. ,
DOI : 10.1016/j.jclinepi.2012.11.008
Regression shrinkage and selection via the Lasso, J R Stat Soc Ser B, vol.58, pp.267-288, 1996. ,
DOI : 10.1111/j.1467-9868.2011.00771.x
Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models, International Journal of Radiation Oncology*Biology*Physics, vol.82, issue.4, pp.677-684, 2012. ,
DOI : 10.1016/j.ijrobp.2011.09.036
Prescription-Drug-Related Risk in Driving, Epidemiology, vol.23, issue.5, pp.706-712, 2012. ,
DOI : 10.1097/EDE.0b013e31825fa528
URL : https://hal.archives-ouvertes.fr/hal-00742317
Integrative study of pandemic A/H1N1 influenza infections: design and methods of the CoPanFlu-France cohort, BMC Public Health, vol.10, issue.1, p.417, 2012. ,
DOI : 10.1186/1471-2334-10-301
URL : https://hal.archives-ouvertes.fr/inserm-00730688
RespiFinder: a New Multiparameter Test To Differentially Identify Fifteen Respiratory Viruses, Journal of Clinical Microbiology, vol.46, issue.4, pp.1232-1240, 2008. ,
DOI : 10.1128/JCM.02294-07
URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2292964
Committee for proprietary medicinal products Note for guidance on harmonization of requirements for influenza vaccines, 2009. ,
Factors Associated with Post-Seasonal Serological Titer and Risk Factors for Infection with the Pandemic A/H1N1 Virus in the French General Population, PLoS ONE, vol.6, issue.4, p.60127, 2013. ,
DOI : 10.1371/journal.pone.0060127.s002
URL : https://hal.archives-ouvertes.fr/hal-01122215
Greedy function approximation: a gradient boosting machine, pp.1189-1232, 2001. ,
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2009. ,
Stochastic gradient boosting, Computational Statistics & Data Analysis, vol.38, issue.4, pp.367-378, 2002. ,
DOI : 10.1016/S0167-9473(01)00065-2
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.31.1666
Generalized Linear Models, 1989. ,
Regularization Paths for Generalized Linear Models via Coordinate Descent, Journal of Statistical Software, vol.33, issue.1, pp.1-22, 2010. ,
DOI : 10.18637/jss.v033.i01
URL : http://doi.org/10.18637/jss.v033.i01
Bootstrap Methods and Permutation Tests, Introd to Pract Stat, 2005. ,
Permutation importance: a corrected feature importance measure, Bioinformatics, vol.26, issue.10, pp.1340-1347, 2010. ,
DOI : 10.1093/bioinformatics/btq134
The mutual information: Detecting and evaluating dependencies between variables, Bioinformatics, vol.18, issue.Suppl 2, pp.231-240, 2002. ,
DOI : 10.1093/bioinformatics/18.suppl_2.S231
Classification and regression by randomForest, pp.18-22, 2002. ,
Generalized boosted models: a guide to the gbm package, pp.1-12, 2007. ,
Data mining in the Life Sciences with Random Forest: a walk in the park or lost in the jungle?, Briefings in Bioinformatics, vol.14, issue.3, pp.315-326, 2013. ,
DOI : 10.1093/bib/bbs034
Classification with correlated features: unreliability of feature ranking and solutions, Bioinformatics, vol.27, issue.14, pp.1986-1994, 2011. ,
DOI : 10.1093/bioinformatics/btr300
Adjusting for multiple testing???when and how?, Journal of Clinical Epidemiology, vol.54, issue.4, pp.343-349, 2001. ,
DOI : 10.1016/S0895-4356(00)00314-0
Multiple test procedures other than Bonferroni's deserve wider use, BMJ, vol.318, issue.7183, pp.600-601, 1999. ,
DOI : 10.1136/bmj.318.7183.600a
Regularization and variable selection via the elastic net, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.5, issue.2, pp.301-320, 2005. ,
DOI : 10.1073/pnas.201162998
Estimation of the Association Between Antibody Titers and Protection Against Confirmed Influenza Virus Infection in Children, Journal of Infectious Diseases, vol.208, issue.8, pp.1320-1324, 2013. ,
DOI : 10.1093/infdis/jit372
Epidemiological Characteristics of 2009 (H1N1) Pandemic Influenza Based on Paired Sera from a Longitudinal Community Cohort Study, PLoS Medicine, vol.361, issue.6, p.1000442, 2011. ,
DOI : 10.1371/journal.pmed.1000442.s009
Findings from a household randomized controlled trial of hand washing and face masks to reduce influenza transmission in Bangkok, Thailand, Influenza and Other Respiratory Viruses, vol.366, issue.4, pp.256-267, 2011. ,
DOI : 10.1111/j.1750-2659.2011.00205.x
Increased H1N1 Infection Rate in Children with Asthma, American Journal of Respiratory and Critical Care Medicine, vol.185, issue.12, pp.1275-1279, 2012. ,
DOI : 10.1164/rccm.201109-1635OC