Improving classification of microarray data using prototype-based feature selection. - Blaise Hanczar; Mélanie Courtine; Arriel Benis; Corneliu Henegar; Karine Clément; Jean-Daniel Zucker (SIGKDD Explor., 2003)

Exploiter l'information mutuelle inter-gènes pour réduire la dimension des données biopuces: une approche basée sur la construction automatique d'attributs. - Blaise Hanczar; Jean-Daniel Zucker (CAP, 2005)

Combining Feature Selection and Feature Construction to Improve Concept Learning for High Dimensional Data. - Blaise Hanczar (SARA, 2005)

Feature construction from synergic pairs to improve microarray-based classification. - Blaise Hanczar; Jean-Daniel Zucker; Corneliu Henegar; Lorenza Saitta (Bioinform., 2007)

Decorrelation of the True and Estimated Classifier Errors in High-Dimensional Settings. - Blaise Hanczar; Jianping Hua; Edward R. Dougherty (EURASIP J. Bioinform. Syst. Biol., 2007)

Classification with reject option in gene expression data. - Blaise Hanczar; Edward R. Dougherty (Bioinform., 2008)

Bagged Biclustering for Microarray Data. - Blaise Hanczar; Mohamed Nadif (ECAI, 2010)

Bagging for Biclustering: Application to Microarray Data. - Blaise Hanczar; Mohamed Nadif (ECML/PKDD (1), 2010)

Small-sample precision of ROC-related estimates. - Blaise Hanczar; Jianping Hua; Chao Sima; John N. Weinstein; Michael L. Bittner; Edward R. Dougherty (Bioinform., 2010)

Exploring interaction measures to identify informative pairs of genes. - Blaise Hanczar; Corneliu Henegar; Jean-Daniel Zucker (Int. J. Bioinform. Res. Appl., 2010)

Accuracy-Rejection Curves (ARCs) for Comparing Classification Methods with a Reject Option. - Malik Sajjad Ahmed Nadeem; Jean-Daniel Zucker; Blaise Hanczar (MLSB, 2010)

Improving the Biological Relevance of Biclustering for Microarray Data in Using Ensemble Methods. - Blaise Hanczar; Mohamed Nadif (DEXA Workshops, 2011)

Using the bagging approach for biclustering of gene expression data. - Blaise Hanczar; Mohamed Nadif (Neurocomputing, 2011)

Experimental analysis of feature selection stability for high-dimension and low-sample size gene expression classification task. - David Dernoncourt; Blaise Hanczar; Jean-Daniel Zucker (BIBE, 2012)

Ensemble methods for biclustering tasks. - Blaise Hanczar; Mohamed Nadif (Pattern Recognit., 2012)

A New Measure of Classifier Performance for Gene Expression Data. - Blaise Hanczar; Avner Bar-Hen (IEEE ACM Trans. Comput. Biol. Bioinform., 2012)

Precision-recall space to correct external indices for biclustering. - Blaise Hanczar; Mohamed Nadif (ICML (2), 2013)

The reliability of estimated confidence intervals for classification error rates when only a single sample is available. - Blaise Hanczar; Edward R. Dougherty (Pattern Recognit., 2013)

Stability of Ensemble Feature Selection on High-Dimension and Low-Sample Size Data - Influence of the Aggregation Method. - David Dernoncourt; Blaise Hanczar; Jean-Daniel Zucker (ICPRAM, 2014)

Unsupervised Consensus Functions Applied to Ensemble Biclustering. - Blaise Hanczar; Mohamed Nadif (ICPRAM, 2014)

Aggregation of Biclustering Solutions for Ensemble Approach. - Blaise Hanczar; Mohamed Nadif (ICPRAM (Selected Papers), 2014)

Combination of One-Class Support Vector Machines for Classification with Reject Option. - Blaise Hanczar; Michèle Sebag (ECML/PKDD (1), 2014)

Analysis of feature selection stability on high dimension and small sample data. - David Dernoncourt; Blaise Hanczar; Jean-Daniel Zucker (Comput. Stat. Data Anal., 2014)

Compromis précision-rappel dans l'évaluation des performances. - Blaise Hanczar; Mohamed Nadif (EGC, 2015)

Controlling the Cost of Prediction in using a Cascade of Reject Classifiers for Personalized Medicine. - Blaise Hanczar; Avner Bar-Hen (BIOINFORMATICS, 2016)

Controlling and Visualizing the Precision-Recall Tradeoff for External Performance Indices. - Blaise Hanczar; Mohamed Nadif (ECML/PKDD (1), 2018)

An approach to optimizing abstaining area for small sample data classification. - Blaise Hanczar; Jean-Daniel Zucker (Expert Syst. Appl., 2018)

An Encoding Adversarial Network for Anomaly Detection. - Elies Gherbi; Blaise Hanczar; Jean-Christophe Janodet; Witold Klaudel (ACML, 2019)

Interpretable Cascade Classifiers with Abstention. - Matthieu Clertant; Nataliya Sokolovska; Yann Chevaleyre; Blaise Hanczar (AISTATS, 2019)

Performance visualization spaces for classification with rejection option. - Blaise Hanczar (Pattern Recognit., 2019)

Deep Learning for In-Vehicle Intrusion Detection System. - Elies Gherbi; Blaise Hanczar; Jean-Christophe Janodet; Witold Klaudel (ICONIP (4), 2020)

Biological interpretation of deep neural network for phenotype prediction based on gene expression. - Blaise Hanczar; Farida Zehraoui; Tina Issa; Mathieu Arles (BMC Bioinform., 2020)

Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data. - Victoria Bourgeais; Farida Zehraoui; Mohamed Ben Hamdoune; Blaise Hanczar (BMC Bioinform., 2021)

CASCARO: Cascade of classifiers for minimizing the cost of prediction. - Blaise Hanczar; Avner Bar-Hen (Pattern Recognit. Lett., 2021)

GraphGONet: a self-explaining neural network encapsulating the Gene Ontology graph for phenotype prediction on gene expression. - Victoria Bourgeais; Farida Zehraoui; Blaise Hanczar (Bioinform., 2022)

Assessment of deep learning and transfer learning for cancer prediction based on gene expression data. - Blaise Hanczar; Victoria Bourgeais; Farida Zehraoui (BMC Bioinform., 2022)

SurvCaus : Representation Balancing for Survival Causal Inference. - Ayoub Abraich; Agathe Guilloux; Blaise Hanczar (CoRR, 2022)

AttOmics: attention-based architecture for diagnosis and prognosis from omics data. - Aurélien Beaude; Milad Rafiee Vahid; Franck Augé; Farida Zehraoui; Blaise Hanczar (Bioinform., 2023)

GAN-based data augmentation for transcriptomics: survey and comparative assessment. - Alice Lacan; Michèle Sebag; Blaise Hanczar (Bioinform., 2023)

Frugal Generative Modeling for Tabular Data. - Alice Lacan; Blaise Hanczar; Michèle Sebag (ECML/PKDD (8), 2024)

ECGrecover: A Deep Learning Approach for Electrocardiogram Signal Completion. - Alex Lence; Federica Granese; Ahmad Fall; Blaise Hanczar; Joe-Elie Salem; Jean-Daniel Zucker; Edi Prifti (KDD (1), 2025)

IKrNet: A Neural Network for Detecting Specific Drug-Induced Patterns in Electrocardiograms Amidst Physiological Variability. - Ahmad Fall; Federica Granese; Alex Lence; Dominique Fourer; Blaise Hanczar; Joe-Elie Salem; Jean-Daniel Zucker; Edi Prifti (CoRR, 2025)

Self-supervised learning on gene expression data. - Kevin Dradjat; Massinissa Hamidi; Pierre Bartet; Blaise Hanczar (CoRR, 2025)