Author

Moses Guddah

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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