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作 者:张儒奇 赵一丁 王盛春 ZHANG Ruqi;ZHAO Yiding;WANG Shengchun(School of Acupuncture-Moxibustion and Tuina,Shandong University of TCM,Jinan 250014,China;Department of Acupuncture-Moxibustion,Physiotherapy and Rehabilitation,Shandong Provincial Hospital Affiliated to First Medical University of Shandong,Jinan 250021)
机构地区:[1]山东中医药大学针灸推拿学院,济南250014 [2]山东第一医科大学附属省立医院针灸理疗康复科,济南250021
出 处:《中国针灸》2025年第4期428-434,共7页Chinese Acupuncture & Moxibustion
基 金:山东省卫生健康委员会齐鲁医派中医学术流派传承项目:鲁卫函[2020]132号;山东省卫生健康委员会齐鲁卫生与健康领军人才培育工程项目:鲁卫人字[2020]3号。
摘 要:脑电图、磁共振成像等神经影像学技术从脑结构、功能、代谢及血流动力学角度为针灸脑效应机制分析提供了客观、可视化技术手段。人工智能算法的发展可弥补神经影像学数据多而分散、质量参差不齐及图像信息高异质性等不足。两者结合应用则可促进针灸效应的个体化、智能化、精准化预测,实现针灸效应差异性应答情况的智能分类,以及脑区激活模式的识别。本文以脑电图、磁共振成像技术为主,分析机器学习、深度学习等人工智能算法对于多模态神经影像数据的优化过程,以及在针灸脑效应机制研究中的应用,并阐明当前研究的空白与局限性,以期为今后针灸脑效应机制研究提供思路。Electroencephalography(EEG)and magnetic resonance imaging(MRI),as neuroimaging technologies,provided objective and visualized technical tools for analyzing the brain effect mechanisms of acupuncture and moxibustion from the perspectives of brain structure,function,metabolism,and hemodynamics.The advancement of artificial intelligence(Al)algorithms can compensate for issues such as the large and scattered nature of neuroimaging data,inconsistent quality,and high heterogeneity of image information.The integration of AI with neuroimaging can facilitate individualized,intelligent,and precise prediction of acupuncture and moxibustion effects,enable intelligent classification of differential acupuncture responses,and identify brain activation patterns.This paper focuses on EEG and MRI,analyzing how machine learning and deep learning optimize multimodal neuroimaging data and their applications in the study of acupuncture and moxibustion brain effects mechanisms.Furthermore,it highlights current research gaps and limitations to provide insights for future studies on acupuncture brain effects mechanisms.
分 类 号:R245[医药卫生—针灸推拿学]
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