超越分类准确率：Neural-MedBench 与深层推理基准的必要性
ICLR 2026 Poster accepted paper at ICLR 2026. Epilepsy affects over 50 million people worldwide, and one-third of patients suffer drug-resistant seizures where surgery offers the best chance of seizure freedom. Accurate localization of the epileptogenic zone (EZ) relies on intracranial EEG (iEEG). Clinical workflows, however, remain constrained by labor-intensive manual review. At the same time, existing data-driven approaches are typically developed on single-center datasets that are inconsistent in format and metadata, lack standardized benchmarks, and rarely release pathological event annotations, creating barriers to reproducibility, cross-center validation, and clinical relevance. Code/project link: https://omni-ieeg.github.io/omni-ieeg/; https://github.com/Omni-iEEG/Omni-iEEG