D. Siegismund, V. Tolkachev, S. Heyse, B. Sick, O. Duerr et al., Developing deep learning applications for life science and pharma industry, Drug Res (Stuttg), vol.68, issue.06, p.305, 2018.

B. Dubuisson and M. Masson, A statistical decision rule with incomplete knowledge about the classes, 1993.

M. E. Hellman, The nearest neighbor classification rule with a reject option, IEEE Trans. Systems Science and Cybernetics, vol.6, pp.179-185, 1970.

C. Dalitz, Reject options and confidence measures for knn classifiers, Schriftenreihe des Fachbereichs Elektrotechnik und Informatik der Hochschule Niederrhein, vol.8, pp.16-38, 2009.

C. Chow, On optimum recognition error and reject tradeoff, IEEE Transactions on Information Theory, vol.16, issue.1, pp.41-46, 1970.

G. C. Vasconcelos, M. C. Fairhurst, and D. Bisset, Investigating feedforward neural networks with respect to the rejection of spurious patterns, Pattern Recognition Letters, vol.16, pp.207-212, 1995.

C. D. Stefano, C. Sansone, and M. Vento, To reject or not to reject: that is the question-an answer in case of neural classifiers, IEEE Trans. Systems, Man, and Cybernetics, Part C, vol.30, pp.84-94, 2000.

A. Brew, M. Grimaldi, and P. Cunningham, An evaluation of one-class classification techniques for speaker verification, Artificial Intelligence Review, vol.27, issue.4, pp.295-307, 2007.

C. Biernacki, G. Celeux, and G. Govaert, Assessing a Mixture Model for Clustering with the Integrated Classification Likelihood, INRIA, 1998.
URL : https://hal.archives-ouvertes.fr/inria-00073163

S. Sperandei, Understanding logistic regression analysis, Biochemia medica, vol.24, issue.1, pp.12-18, 2014.

H. Shin, H. R. Roth, M. Gao, L. Lu, Z. Xu et al., Deep convolutional neural networks for computer-aided detection: Cnn architectures, dataset characteristics and transfer learning, IEEE transactions on medical imaging, vol.35, issue.5, pp.1285-1298, 2016.

A. G. Howard, M. Zhu, B. Chen, D. Kalenichenko, W. Wang et al., Mobilenets: Efficient convolutional neural networks for mobile vision applications, 2017.

J. Deng, W. Dong, R. Socher, L. Li, K. Li et al., ImageNet: A Large-Scale Hierarchical Image Database, p.9, 2009.

I. Jolliffe, Principal Component Analysis, ser. Springer Series in Statistics, 2006.

A. Criminisi, E. Konukoglu, and J. Shotton, Decision forests for classification, regression, density estimation, manifold learning and semi-supervised learning, 2011.

F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion et al., Scikit-learn: Machine learning in Python, Journal of Machine Learning Research, vol.12, pp.2825-2830, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00650905

P. J. Green, Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrika, vol.82, issue.4, pp.711-732, 1995.