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Publications

Found 321 results
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2006
Sotiriou C, Wirapati P, Loi SM, Desmedt C, Durbecq V, Harris A, Bergh J, Smeds J, Haibe-Kains B, Larsimont D, et al. Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis. Journal of National Cancer Institute. 2006:262-272.
Sotiriou C, Wirapati P, Loi S, Haibe-Kains B, Piette F, Buyse M, Bontempi G, Delorenzi M, Piccart M. Is genomic grading killing histological grading ?. In: Journal of European Breast Cancer. Vol. 4. Journal of European Breast Cancer. ; 2006. p. 177.
Bersini H, Lenaerts T, Santos FC. Growing biological networks: beyond the gene-duplication model. Journal of Theoretical Biology [Internet]. 2006:488–505.
Caelen O, Bontempi G, Coussaert E, Barvais L, Clement F. Machine Learning Techniques to Enable Closed-Loop Control in Anesthesia.
Caelen O, Engelman E, Schmartz D, Bontempi G, Barvais L. Preliminary Results of Data Mining in BIS guided Propofol-Remifentanil TCI Anaesthesia(abstract).
Bejjani G, Caelen O, Bontempi G, Perrin L, Barvais L. Retrospective comparison of manual versus semi-automated propofol-remifentanil TCI Anaesthesia (abstract).
Kontos K, Bontempi G. Scale-free paradigm in yeast genetic regulatory network inferred from microarray data. In: Kovacs T, Marshall JAR Proceedings of AISB'06: Adaptation in Artificial and Biological Systems. Vol. 3. Proceedings of AISB'06: Adaptation in Artificial and Biological Systems. ; 2006. p. 139-144.
Le Borgne Y, Moussaid M, Bontempi G. Simulation Architecture for Data Processing Algorithms in Wireless Sensor Networks.
Caelen O, Bontempi G, Clement F, Coussaert E, Barvais L. Simulation assessment of a closed-loop controller designed by machine learning techniques(abstract).
Cilia E, Moschitti A, Ammendola S, Basili R. Structured Kernels for the Automatic Detection of Protein Active Sites. Proceedings of Mining and Learning with Graphs@ECML/PDKK [Internet]. 2006.
2005
Bontempi G, Le Borgne Y. An Adaptive Modular Approach to the Mining of Sensor Network Data.
Bontempi G, Le Borgne Y. An Adaptive Modular Approach to the Mining of Sensor Network Data.
Sotiriou C, Wirapati P, Loi S, Desmedt C, Durbecq V, Harris A, Bergh J, Smeds J, Haibe-Kains B, Larsimont D, et al. Better characterization of estrogen receptor (ER) positive luminal subtypes using genomic grade. In: Breast Cancer Research and Treatment. Vol. 94. Breast Cancer Research and Treatment. ; 2005. p. S19.
Le Borgne Y. Bias-variance Trade-Off Characterization in a Classification Problem. What Differences with Regression?.
Sotiriou C, Wirapati P, Loi SM, Desmedt C, Durbecq V, Harris A, Bergh J, Smeds J, Haibe-Kains B, Larsimont D, et al. Breast tumours with intermediate histological grade can be reclassified into prognostically distinct groups by gene expression profiling. In: Breast Cancer Research and Treatment. Vol. 94. Breast Cancer Research and Treatment. ; 2005. p. S30.
Bontempi G, Birattari M, Meyer PE. Combining Lazy Learning, Racing and Subsampling for Effective Feature Selection.
Chu D, Lee H-C, Lenaerts T. Evolution of DNA uptake signal sequences. Artif Life [Internet]. 2005:317–38.
Lenaerts T, Jansen B, Tuyls K, Vylder BD. The evolutionary language game: an orthogonal approach. Journal of Theoretical Biology [Internet]. 2005:566–82.
Desmedt C, Loi SM, Haibe-Kains B, Soree A, Lallemand F, Durbecq V, Larsimont D, Tutt A, Ellis P, Gillett C, et al. Four genes by RT-PCR predicts distant relapse for women given adjuvant tamoxifen. In: Breast Cancer Research and Treatment. Vol. 94. Breast Cancer Research and Treatment. ; 2005. p. S129.
Bontempi G, Birattari M. From Linearization to Lazy Learning: A Survey of Divide-and-Conquer Techniques for Nonlinear Control. International Journal of Computational Cognition. 2005:56-73.
Sotiriou C, Wirapati P, Loi S, Harris A, Bergh J, Smeds J, Farmer P, Praz V, Haibe-Kains B, Lallemand F, et al. Gene Expression Profiling in Breast Cancer Challenges the Existence of Intermediate Histological Grade.
Caelen O, Bontempi G. How to allocate a restricted budget of leave-one-out assessments for effective model selection in machine learning: a comparison of state-of-the-art techniques.
Loi S, Desmedt C, Haibe-Kains B, Lallemand F, Gillett C, Tutt A, Ryder K, Ellis P, Harris A, Smeds J, et al. Predicting relapse in estrogen receptor (ER) positive breast cancer (luminal) subgroups treated with adjuvant tamoxifen. In: Breast Cancer Research and Treatment. Vol. 94. Breast Cancer Research and Treatment. ; 2005. p. S129.
Loi S, Piccart M, Haibe-Kains B, Desmedt C, A.Harris, Bergh J, Ellis P, Miller L, Liu E, Sotiriou C, et al. Prediction of early distant relapses on tamoxifen in early- stage breast cancer (BC): a potential tool for adjuvant aromatase inhibitor (AI) tailoring.
Villacci D, Bontempi G, Vaccaro A, Birattari M. The role of learning methods in the dynamic assessment of power components loading capability. IEEE Transactions on Industrial Electronics. 2005.

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