发表机构
Vietnam Maritime University; HAISmartlink Lab（越南海事大学; HAISmartlink实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对临床EEG报告依赖人工、现有工具无法满足AI训练需求的问题，提出EEG-to-Report框架，整合多格式EEG处理与标注，生成对齐特征-文本对，还含自动报告模块，为自动化EEG报告系统提供基础。
AI 中文摘要
临床脑电图（EEG）报告目前仍以人工为主，耗时巨大，且现有EEG软件生态系统无法生成训练现代语言模型所需的结构化EEG-文本监督数据。大多数工具包仅关注可视化或预处理，对生成高质量AI数据集的工作流程支持有限。我们提出EEG-to-Report，这是一个基于浏览器的标注与特征-文本框架，将常规EEG审阅与AI就绪数据集的构建相结合。该框架整合了多格式EEG导入、通道标准化，以及带有多模态标注层的交互式查看器，该标注层结合了结构化文本与转录语音笔记。对于每个标注片段，特征提取引擎会计算一组标准化的频谱、时域、熵、Hjorth、连接性及尖峰相关描述符，与临床描述一同存储在可移植JSON模式中，从而生成用于监督多模态EEG-语言模型的对齐特征-文本对。该框架还包含自动报告模块，其结合了卷积网络集成与大型语言模型，以生成供神经科医生审阅的临床叙述。利用试点标注，我们描述了EEG-to-Report如何简化标注工作流程并生成可编辑的报告草稿，为自动化EEG报告系统提供了可复用的基础。
英文摘要
Clinical electroencephalography (EEG) reporting remains largely manual and time-consuming, and current EEG software ecosystems do not produce the structured EEG-text supervision needed for training modern language models. Most toolboxes focus on visualization or preprocessing, providing limited support for workflows that generate high-quality datasets for AI. We introduce EEG-to-Report, a browser-based annotation and feature-text framework that links routine EEG review with the construction of AI-ready datasets. The framework integrates multi-format EEG ingestion, channel standardization, and an interactive viewer with a multimodal annotation layer that combines typed text and transcribed voice notes. For each annotated segment, a feature extraction engine computes a standardized set of spectral, temporal, entropy, Hjorth, connectivity, and spike-related descriptors, stored alongside clinical descriptions in a portable JSON schema. This yields aligned feature-text pairs designed to supervise multimodal EEG-language models. The framework also includes an auto-report module that couples an ensemble of convolutional networks with a large language model to draft clinical narratives for neurologist review. Using pilot annotations, we describe how EEG-to-Report streamlines annotation workflows and produces editable draft reports, providing a reusable foundation for automated EEG reporting systems.
