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S. Ziti

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Open access 2026

CMST-FL: Cross-Missingness Stable Trust with Evidence-Guided Preprocessing for Federated Healthcare Signal Imputation

Missing physiological samples create preprocessing uncertainty and uneven client reliability in federated learning. This study proposes Cross-Missingness Stable Trust federated learning (CMST-FL), a two-stage framework that selects an imputer using development patients and then weights local updates from their marginal...

Benachir Rigalma, S. Ziti, M. Belhiah et al. · 0 citations
Open access 2026

AI-Based Preprocessing and R-Squared Weighted Federated Aggregation for Robust Healthcare Signal Imputation

This work presents an AI based preprocessing framework that combines advanced imputation methods, including K Nearest Neighbors (KNN), Autoencoder reconstruction, and Generative Adversarial Networks (GAN), with classical baselines such as mean and median imputation to provide robust convergence and stability in federat...

Benachir Rigalma, Hamid Ouhnni, M. Belhiah et al. · 0 citations
#small language model Review Sep 2026

FHIR as an interoperability enabler for clinical applications: a narrative review of implementations, impacts, and future challenges.

FHIR has successfully catalyzed widespread technical innovation and serves as the foundation for advanced clinical applications, however, a significant translational gap persists and future efforts should expand beyond technical development.

Wafae Abbaoui, S. Ziti, Sara Retal · 0 citations
Open access Jul 2026

Integrating Multi-Source Pulmonary X-Ray Data into a Cross-Validated CNN with AdamW and Augmentation

This study presents an approach for classifying lung diseases using a tailored convolutional neural network (CNN) that combines several chest X-ray (CXR) datasets and applies extensive data augmentation to build a balanced dataset and improve generalization.

Fouad Issouani, Ayyad Maafiri, S. Ziti · 0 citations

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