Publications

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H. Benhar, Idri, A., et Fernández-Alemán, J. L., « Data preprocessing for heart disease classification: A systematic literature review. », Computer Methods and Programs in Biomedicine, vol. 195, 2020.
H. Benhar, Hosni, M., et Idri, A., « Univariate and Multivariate Filter Feature Selection for Heart Disease Classification », Journal of Information Science and Engineering, vol. 38, p. 791-803, 2022.
H. Benhar, Idri, A., et Hosni, M., « Impact of threshold values for filter-based univariate feature selection in heart disease classification », in HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020, 2020, p. 391-398.
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I. Chlioui, Abnane, I., et Idri, A., « Comparing Statistical and Machine Learning Imputation Techniques in Breast Cancer Classification », Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12252 LNCS, p. 61-76, 2020.
I. Chlioui, Idri, A., Abnane, I., et EZZAT, M., « Ensemble case based reasoning imputation in breast cancer classification », Journal of Information Science and Engineering, vol. 37, p. 1039-1051, 2021.
I. Chlioui, Idri, A., et Abnane, I., « Data preprocessing in knowledge discovery in breast cancer: systematic mapping study », Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, vol. 8, p. 547-561, 2020.
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B. ElOuassif, Idri, A., Hosni, M., et Abran, A., « Classification techniques in breast cancer diagnosis: A systematic literature review », Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, vol. 9, p. 50-77, 2021.
M. EZZAT et Idri, A., « Reviewing Data Analytics Techniques in Breast Cancer Treatment », Advances in Intelligent Systems and Computing, vol. 1161 AISC, p. 65-75, 2020.
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F. - Z. Nakach, Zerouaoui, H., et Idri, A., « Random Forest Based Deep Hybrid Architecture for Histopathological Breast Cancer Images Classification », Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13376 LNCS, p. 3-18, 2022.
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E. B. Ouassif, Idri, A., et Hosni, M., « Homogeneous ensemble based support vector machine in breast cancer diagnosis », in HEALTHINF 2021 - 14th International Conference on Health Informatics; Part of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2021, 2021, p. 352-360.
E. B. Ouassif, Idri, A., et Hosni, M., « Investigating Accuracy and Diversity in Heterogeneous Ensembles for Breast Cancer Classification », Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12950 LNCS, p. 263-281, 2021.
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K. Sanak, Azzouzi, M., Abik, M., et Radouani, F., « MARCO Gene Variations and Their Association with Cardiovascular Diseases Development: An In-Silico Analysis », Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12108 LNBI, p. 203-212, 2020.
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H. Zerouaoui, Idri, A., et O. Alaoui, E., « A new approach for histological classification of breast cancer using deep hybrid heterogenous ensemble », Data Technologies and Applications, p. 1-34, 2022.
H. Zerouaoui, Idri, A., Nakach, F. Z., et Hadri, R. E., « Breast Fine Needle Cytological Classification Using Deep Hybrid Architectures », Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12950 LNCS, p. 186-202, 2021.
H. Zerouaoui, Idri, A., et K. Asnaoui, E., « Machine Learning and Image Processing for Breast Cancer: A Systematic Map », Advances in Intelligent Systems and Computing, vol. 1161 AISC, p. 44-53, 2020.
H. Zerouaoui et Idri, A., « Deep hybrid architectures for binary classification of medical breast cancer images », Biomedical Signal Processing and Control, vol. 71, 2022.

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