V. Vovk, A. Gammerman, and G. Shafer, Algorithmic Learning in a Random World, 2005.

A. Gammerman, V. Vovk, and V. Vapnik, Learning by Transduction, 14th Conference on Uncertainty in Artificial Intelligence, pp.148-155, 1998.

K. Proedrou, I. Nouretdinov, V. Vovk, and A. Gammerman, Transductive Confidence Machines for Pattern Recognition, 2001.
DOI : 10.1007/3-540-36755-1_32

URL : http://www.clrc.rhbnc.ac.uk/tech-report/files/tr0102.ps

L. Breiman, Random Forests, Machine Learning, vol.45, issue.1, pp.5-32, 2001.
DOI : 10.1023/A:1010933404324

L. Breiman and A. Cutler, Random Forests

J. F. Timms, R. Cramer, S. Camuzeaux, A. Tiss, C. Smith et al., Peptides Generated Ex Vivo from Serum Proteins by Tumor-Specific Exopeptidases Are Not Useful Biomarkers in Ovarian Cancer, Clinical Chemistry, vol.56, issue.2, pp.262-271, 2010.
DOI : 10.1373/clinchem.2009.133363

URL : http://clinchem.aaccjnls.org/content/clinchem/56/2/262.full.pdf

A. Gammerman, I. Nouretdinov, B. Burford, A. Chervonenkis, V. Vovk et al., Clinical Mass Spectrometry Proteomic Diagnosis by Conformal Predictors, Statistical Applications in Genetics and Molecular Biology, vol.7, issue.2, p.13, 2008.
DOI : 10.2202/1544-6115.1385

I. Nouretdinov, B. Burford, Z. Luo, and A. Gammerman, Data Analysis of 7 Biomarkers, 2008.

A. Gammerman and A. R. Thatcher, Bayesian Diagnostic Probabilities without Assuming Independence of Symptoms, Method Inform Med, vol.30, issue.1, pp.15-22, 1991.
DOI : 10.1007/978-1-4613-9052-7_10

I. Nouretdinov, B. Burford, and A. Gammerman, Application of Inductive Confidence Machine to ICMLA Competition Data, 2009 International Conference on Machine Learning and Applications, pp.435-438, 2009.
DOI : 10.1109/ICMLA.2009.24