Author

Adham Atyabi

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Open access Sep 2026

Explainable Hybrid GRU–TabTransformer Learning with Cross-Attention and LLM-Assisted Interpretation for Stroke Risk Prediction

A hybrid Gated Recurrent Unit-TabTransformer architecture using cross-attention for stroke-status prediction and Large Language Models and LLM-based explainability to support interpretable stroke risk prediction systems is proposed, pending robust external validation before deployment.

Moses Guddah, Adham Atyabi · Applied Informatics · 0 citations

Jul 2026

Multimodal Pretraining for Generalizable EEG Representation Learning

A multimodal EEG foundation model that combines a raw signal encoder based on the Mamba architecture, a Vision Transformer-style encoder for time-frequency data, and a lightweight encoder for text, all within a shared embedding space is developed.

Targol Bakhtiarvand, J. Kalita, Adham Atyabi · arXiv.org · 0 citations