AI 读脑电图：Lancet 综述梳理癫痫诊断自动化进展
Artificial intelligence models for automated and semiautomated analysis and interpretation of clinical electroencephalography
Lancet 这篇综述讲 AI 怎么读脑电图，做医疗 AI 或关心癫痫诊断的同行可以翻翻。
The Lancet Digital Health 刊发综述，聚焦人工神经网络在临床 EEG（脑电图）自动与半自动判读中的应用。
EEG 是癫痫最常用的诊断工具，但专业判读能力并不普及。数字技术与可穿戴设备推动大规模 EEG 采集，数据量已超出专家目视判读的承载能力。
综述认为 AI 应增强人类专家并降低工作负荷，AI 判读 EEG 因此更接近临床实施。
Artificial intelligence models for automated and semiautomated analysis and interpretation of clinical electroencephalography
Electroencephalography is the most commonly used diagnostic tool for epilepsy. However, interpreting electroencephalograms (EEGs) requires expertise that is not widely available. Advances in digital technology and wearables have enabled large-scale EEG recording, generating vast amounts of data that cannot be managed through traditional visual interpretation by experts. Artificial intelligence (AI) has the potential to augment human expertise and reduce workloads. The application of artificial neural networks in analysing clinical EEG recordings has led to major breakthroughs, bringing AI-based EEG interpretation closer to clinical implementation.
本条情报归属 AITOP「论文」核心追踪栏目。涉及核心实体与技术议题包括：EEG、脑电图、癫痫、医疗AI，读者可通过下方标签进入对应专题页查阅历史脉络与关联对比。
信源核验说明：本文原始线索采编自「Lancet Digital Health」（@Sándor Beniczky, Birgit Frauscher, Fábio A Nascimento, Shobi Sivathamboo, Catalina A Rojas, Michael R Sperling, Samden Lhatoo, Philippe Ryvlin, Levin Kuhlmann），经 AITOP 多维评分管线结构化提炼。