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。

Focusing on the core breakthrough of multimodal fused structural and unstructural data in the Clinical-Behavioral-Neurological domain, such multimodal data is rarely available in domestic China. By deeply integrating Electronic Medical Records (EMR), 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 interactions and behavioral features, directly addressing the industry pain points of traditional diagnosis and treatment that relies on subjective rating scales and suffers from severe data silos. The product provides an open adverse reaction warning system, which can accurately identify the strong correlations between drugs such as methylphenidate and atomoxetine and sleep disorders as well as gastrointestinal risks, thereby shortening clinical cycles and reducing R&D costs.

搜集汇总

背景与挑战

背景概述

该数据集是国内罕见的注意缺陷多动障碍（ADHD）多模态数据，整合了临床诊断、神经信号、语义交互与行为特征，用于构建动态分析系统。数据集覆盖全国，每月更新，存储大小为1 TB，适用于医疗健康和科技创新领域。