生物医学工程研究2024，Vol.43Issue(3)：246-255,10.DOI:10.19529/j.cnki.1672-6278.2024.03.10
基于图神经网络的神经精神疾病研究进展
Research progress in neuropsychiatric diseases based on graph neural network
摘要
Abstract
Neuropsychiatric diseases seriously affect the anatomical structure of the brain,nervous system function,and mental health of patients.Early identification and diagnosis are of great significance for the treatment and rehabilitation of patients with neuro-psychiatric diseases.The construction of complex brain networks based on neuroimage data can be used to quantitatively analyze the brain structure and function abnormalities in patients with neuropsychiatric diseases,and provide an important reference for the devel-opment of neuroimaging biomarkers for neuropsychiatric diseases.In recent years,graph neural network has been widely used in the di-agnosis of neuropsychiatric diseases because of their advantages of processing non-Euclidean data and making full use of the topological structure and attributes of nodes and connected edges.We summarize the basic principles of graph convolutional network and the latest research progress in neuropsychiatric diseases,and look forward to research hotspots such as dynamic brain network,large sample and multi center,visualization and interpretability.关键词
磁共振成像/神经精神疾病/脑网络/自动分类/图神经网络/疾病诊断Key words
Magnetic resonance imaging/Neuropsychiatric diseases/Brain network/Automatic classification/Graph neural net-work/Disease diagnosis分类
医药卫生引用本文复制引用
王海源,吴凯,陈小怡,彭润霖,梁丽琴,周静..基于图神经网络的神经精神疾病研究进展[J].生物医学工程研究,2024,43(3):246-255,10.基金项目
广东省科技重点领域研发计划项目(2020B0404010002) （2020B0404010002）
国家重点研发计划(2023YFC2414500,2023YFC2414504) （2023YFC2414500,2023YFC2414504）
国家自然科学基金资助项目(72174082) （72174082）
广东省基础与应用基础研究基金杰出青年项目(2021B1515020064) （2021B1515020064）
广东省基础与应用基础研究基金(2022A1515140142) （2022A1515140142）
广东省教育厅重点实验室项目(2020KSYS001) （2020KSYS001）
广州市科技计划项目(202103000032,202206060005,202206080005,202206010077,202206010034). （202103000032,202206060005,202206080005,202206010077,202206010034）
