Automatic Identification of Diabetes Diseases using an Artificial Immune Recognition System2 (AIRS2) with Fuzzy K-Nearest Neighbor. - Meryem Saidi; Mohammed Amine Chikh; Nesma Settouti (CIIA, 2011)

Diagnosis of Diabetes Diseases Using an Artificial Immune Recognition System2 (AIRS2) with Fuzzy K-nearest Neighbor. - Mohammed Amine Chikh; Meryem Saidi; Nesma Settouti (J. Medical Syst., 2012)

Machine Learning Tool for Automatic ASA Detection. - Mohammed El Amine Lazouni; Mostafa El Habib Daho; Nesma Settouti; Mohammed Amine Chikh; Saïd Mahmoudi (Modeling Approaches and Algorithms for Advanced Computer Applications, 2013)

Weighted vote for trees aggregation in Random Forest. - Mostafa El Habib Daho; Nesma Settouti; Mohammed El Amine Lazouni; Mohammed Amine Chikh (ICMCS, 2014)

Automatic detection of difficult tracheal intubation. - Mohammed El Amine Lazouni; Nesma Settouti; Mostafa El Habib Daho; Saïd Mahmoudi; Mohammed Amine Chikh (ICMCS, 2014)

Application of pixel selection in pixel-based classification for automatic white blood cell segmentation. - Meryem Saidi; Mohammed El Amine Bechar; Nesma Settouti; Mohammed Amine Chikh (MedPRAI, 2016)

Statistical Comparisons of the Top 10 Algorithms in Data Mining for Classi cation Task. - Nesma Settouti; Mohammed El Amine Bechar; Mohammed Amine Chikh (Int. J. Interact. Multim. Artif. Intell., 2016)

The Homogeneous Ensemble Methods for MLknn Algorithm. - Khalida Douibi; Nesma Settouti; Mohammed Amine Chikh (ICCDA, 2017)

Reinforced confidence in self-training for a semi-supervised medical data classification. - Mohammed El Amine Bechar; Nesma Settouti; Mohammed Amine Chikh; Mouloud Adel (Int. J. Appl. Pattern Recognit., 2017)

Using conditional inference forest to identify variable importance. - Nesma Settouti; Mostafa El Habib Daho; Mohammed Amine Chikh (Int. J. Bioinform. Res. Appl., 2017)

A new feature selection approach based on ensemble methods in semi-supervised classification. - Nesma Settouti; Mohammed Amine Chikh; Vincent Barra (Pattern Anal. Appl., 2017)

Comparaison of Ensemble Cost Sensitive Algorithms: Application to Credit Scoring Prediction. - Meryem Saidi; Mostafa El Habib Daho; Nesma Settouti; Mohammed El Amine Bechar (ICAASE, 2018)

Semi-supervised Super-pixels classification for White Blood Cells segmentation. - Mohammed El Amine Bechar; Nesma Settouti; Mostafa El Habib Daho; Mohammed Amine Chikh (PAIS, 2018)

Instances selection algorithm by ensemble margin. - Meryem Saidi; Mohammed El Amine Bechar; Nesma Settouti; Mohammed Amine Chikh (J. Exp. Theor. Artif. Intell., 2018)

Semi-supervised superpixel classification for medical images segmentation: application to detection of glaucoma disease. - Mohammed El Amine Bechar; Nesma Settouti; Vincent Barra; Mohammed Amine Chikh (Multidimens. Syst. Signal Process., 2018)

Semi-Supervised learning with Collaborative Bagged Multi-label K-Nearest-Neighbors. - Nesma Settouti; Khalida Douibi; Mohammed El Amine Bechar; Mostafa El Habib Daho; Meryem Saidi (Open Comput. Sci., 2019)

An instance and variable selection approach in pixel-based classification for automatic white blood cells segmentation. - Nesma Settouti; Meryem Saidi; Mohammed El Amine Bechar; Mostafa El Habib Daho; Mohammed Amine Chikh (Pattern Anal. Appl., 2020)

Pre-trained Backbones Effect on Nuclei Segmentation Performance. - Chifa Maarouf; Mohammed Lamine Benomar; Nesma Settouti (MedPRAI, 2021)

Deep Transfer Learning Techniques for Automated Classification of Histological Childhood Medulloblastoma Images. - Ghezali Waffa; Nesma Settouti (MedPRAI, 2021)

A new correlation-based approach for ensemble selection in random forests. - Mostafa El Habib Daho; Nesma Settouti; Mohammed El Amine Bechar; Amina Boublenza; Mohammed Amine Chikh (Int. J. Intell. Comput. Cybern., 2021)

Analysis of Machine Learning and Deep Learning Frameworks for Opinion Mining on Drug Reviews. - Fatiha Youbi; Nesma Settouti (Comput. J., 2022)

Exploring Sentiment Analysis in Health with CNN, GRU and Zero-Shot Learning on Imbalanced Textual Data. - Souaad Hamza-Cherif; Nesma Settouti (RIF, 2023)

Preliminary analysis of explainable machine learning methods for multiple myeloma chemotherapy treatment recognition. - Nesma Settouti; Meryem Saidi (Evol. Intell., 2024)

Feature importance analysis for a highly unbalanced multiple myeloma data classification. - Rima Guilal; Nesma Settouti; Gonzalo Martínez-Muñoz; Mohammed Amine Chikh (Int. J. Medical Eng. Informatics, 2024)

Identifying regions of interest in whole slide images of renal cell carcinoma. - Mohammed Lamine Benomar; Nesma Settouti; Eric Debreuve; Xavier Descombes; Damien Ambrosetti (CoRR, 2025)