A Graph-Based Information Fusion Approach for ADHD Subtype Classification

计算机科学 图形 人工智能 机器学习 理论计算机科学
作者
Wuliang Huang,Xinlong Jianga,Chenlong Gaoa,Teng Zhanga,Yunbing Xing,Yiqiang Chen,Yi Zheng,Jie Li
标识
DOI:10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00112
摘要

Attention deficit hyperactivity disorder (ADHD) is a common childhood mental disorder that encompasses three subtypes. Classifying each subtype has practical significance. However, the gold standard for subtype diagnosis depends on face-to-face consultation with psychiatrists, which is limited by medical resources. This paper proposes a graph-based multimodal fusion approach to classify each subtype objectively, alleviating the pressure on psychiatrists. The proposed method leverages heterogeneous signals, including motion and speech, which are significant indicators of ADHD. We construct a personal graph where each child is a vertex, and the similarity of their personal information measures edges. Since the associations between subjects modeled by the personal graph provide rich prior knowledge, we regard the problem of subtype classification as predicting the labels of vertices on a graph. A novel graph neural network model is proposed to enable information passing between children, fusing motion and speech features under the guidance of the personal graph. We design a reading scenario and collect a multimodal dataset containing 56 children with ADHD and 50 typically developing children. Results of ADHD subtype classification demonstrate the practical value of the proposed approach. We also perform ablation studies to verify the validity of the proposed method.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
英姑应助Sea_U采纳,获得10
3秒前
金金金完成签到,获得积分10
4秒前
cobo完成签到,获得积分10
5秒前
肖肖发布了新的文献求助10
6秒前
Rondab应助准炮打不准采纳,获得10
7秒前
ran完成签到,获得积分10
7秒前
遇上就这样吧应助YSJ采纳,获得10
8秒前
8秒前
朱1591完成签到,获得积分10
10秒前
研友_VZG7GZ应助战斗暴龙兽采纳,获得10
12秒前
12秒前
12秒前
15秒前
YJ888发布了新的文献求助10
15秒前
c_123发布了新的文献求助10
16秒前
SYLH应助科学宝宝☜采纳,获得10
17秒前
clcl发布了新的文献求助10
17秒前
可爱蓝天完成签到,获得积分10
19秒前
顾矜应助东方红采纳,获得30
19秒前
俭朴的听寒完成签到,获得积分10
20秒前
王了了完成签到 ,获得积分10
21秒前
23秒前
kingyz完成签到,获得积分10
23秒前
tan完成签到,获得积分10
25秒前
27秒前
科研通AI5应助张涛采纳,获得10
27秒前
29秒前
29秒前
香蕉觅云应助冉冉采纳,获得10
30秒前
32秒前
yy发布了新的文献求助10
32秒前
33秒前
瘦瘦天奇发布了新的文献求助10
34秒前
牛马发布了新的文献求助10
36秒前
36秒前
39秒前
归尘应助humorr采纳,获得10
39秒前
yy完成签到,获得积分10
41秒前
东方红发布了新的文献求助30
42秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3988997
求助须知:如何正确求助?哪些是违规求助? 3531351
关于积分的说明 11253520
捐赠科研通 3269928
什么是DOI,文献DOI怎么找? 1804830
邀请新用户注册赠送积分活动 882063
科研通“疑难数据库(出版商)”最低求助积分说明 809068