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该研究使用在 Temple University EEG 语料上预训练的轻量级 CNN–Transformer 基础模型提取个性化潜在动力学，发现癫痫与非癫痫患者即使预测拟合度几乎相同，其学到的潜在依赖结构却存在显著差异，强调个性化临床模型需同时评估预测效度与内部动力学结构。
This paper introduces Manana, a non-parametric prompt-learning framework that teaches LLMs to recommend anti-seizure medications and defer uncertain cases in underrepresented epilepsy care settings, improving accuracy on Ugandan cohorts and enabling selective prediction with high precision.