Author

M. Mbarki

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Open access Sep 2026

Interpretable Machine Learning Frameworks for QSAR Modeling: A Comparative Study of Classical Algorithms and Transformer-CNN Architectures

An interpretable Quantitative Structure–Activity Relationship (QSAR) framework that integrates classical machine learning approaches with a hybrid deep learning architecture to model enzyme inhibition using a curated and diverse data set from ChEMBL is developed.

Fatima Ezzahra Belkhanchi, M. Mbarki, S. Chtita et al. · ACS Omega · 0 citations