注意缺陷多动障碍相关数据

以“临床-行为-神经”多模态融合的结构/非结构数据为核心突破，该领域多模态数据在国内罕见。通过深度融合电子病历、真实世界药物副反应数据及高精度行为日志，构建国内首个整合临床诊断、神经信号、语义交互与行为特征的动态分析系统，直击传统诊疗依赖主观量表、数据孤岛严重的行业痛点。产品可开放不良反应预警系统，可精准识别如哌甲酯、托莫西汀等药物与睡眠障碍、胃肠道风险的强关联性，缩短临床周期，节省研发成本。

Taking the structured/unstructured data for "Clinical-Behavioral-Neurological" multi-modal fusion as the core breakthrough, such multi-modal data is rarely available in China. By deeply integrating electronic medical records (EMRs), real-world adverse drug reaction (ADR) data and high-precision behavioral logs, we have developed the first domestic dynamic analysis system integrating clinical diagnosis, neural signals, semantic interaction and behavioral characteristics, directly addressing the key industry pain points of traditional diagnosis and treatment—over-reliance on subjective rating scales and severe data silos. The system offers an open adverse reaction early warning module, which can accurately identify the strong correlations between drugs such as methylphenidate, atomoxetine and sleep disorders as well as gastrointestinal risks, thereby shortening clinical cycles and reducing research and development costs.

搜集汇总

背景与挑战

背景概述

该数据集是国内首个整合临床诊断、神经信号、语义交互与行为特征的动态分析系统，专注于注意缺陷多动障碍（ADHD）的多模态数据研究，特别适用于药物不良反应预警和临床周期优化。