Author

Mamoun Qjidaa

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Open access Jul 2026

An Interpretable Machine Learning Model for the Differentiation of Liver Cysts and Liver Tumors Based on Computed Tomography (CT) Imaging

An explainable radiomics-based machine learning framework for the non-invasive, accurate, and interpretable discrimination of MLT and PLC, designed to assist radiologists in reducing diagnostic ambiguity and expediting patient management is proposed.

Mamoun Qjidaa, Anass Benfares, Mohammed Amine El Azami El Hassani et al. · Livers · 0 citations

Open access Jul 2026

Automated Differentiation of Hepatic Cysts and Metastatic Tumors Using a Deep Learning Ensemble Framework on CT Imaging in Low-Resource Areas

This approach offers a practical and reliable way to classify hepatic lesions with minimal manual intervention and may help improve consistency in diagnosis and could be integrated into clinical workflows to support decision making in low-resource areas.

Mamoun Qjidaa, Amine Souadka, Anass Benfares et al. · BioMedInformatics · 0 citations