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Neuro-Oracle is a trajectory-aware agentic Retrieval-Augmented Generation (RAG) framework for interpretable epilepsy surgical prognosis, proposed in 2026 by computer scientist Aizierjiang Aiersilan and neurologist Mohamad Z. Koubeissi, MD (Chair of Neurology and Director of the Epilepsy Center at The George Washington University).

Instead of judging a patient from one pre-operative MRI, Neuro-Oracle reads the change between two scans. A 3D Siamese ResNet-50 encoder distils paired pre- and post-operative T1-weighted MRIs into a 512-dimensional "trajectory vector." That vector queries a population archive of past cases via cosine nearest-neighbour search (FAISS), and a 4-bit quantized Llama-3-8B agent reasons over the retrieved evidence to output a SUCCESS / FAILURE verdict with a natural-language justification — an auditable prognosis instead of a black-box score.

On the public EPISURG dataset (N=268, five-fold cross-validation), trajectory-based variants reach AUC 0.834–0.905 versus 0.793 for a single-scan ResNet-50 baseline. The Neuro-Oracle agent reaches AUC 0.867 with zero observed hallucinations under the authors' audit.

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