摘要
肠道微生物与大脑之间的双向沟通机制称为肠-脑轴,肠-脑轴的紊乱与多种常见疾病相关,但目前临床确诊方法不完善。静息态功能磁共振成像(resting state functional MRI, rs-fMRI)技术作为重要的影像学工具,帮助提供脑部的功能变化情况;机器学习通过不同的特征提取方法、分类算法等建立预测模型,二者结合常应用于疾病的诊断、分类和预后等方面。本文综述了rs-fMRI结合机器学习应用于肠-脑轴相关的胃肠及主要神经类疾病的研究,旨在为相关模型建立、辅助临床诊断、实现精准医疗提供技术参考。
The two-way communication between gut microbes and the brain is called the gut-brain axis.Disorders of the gut-brain axis are associated with many diseases.However,the current clinical diagnosis method is not perfect.Resting state functional magnetic resonance imaging(rs-fMRI)is an important imaging tool that helps provide information about changes in brain function;machine learning builds prediction models by selecting different feature extraction methods and classification algorithms.The combination of the two is often used in the diagnosis,classification and prognosis of diseases.This article reviews the application of rs-fMRI combined with machine learning to gastrointestinal and major neurological diseases related to the gut-brain axis,aims to provide technical reference for the establishment of relevant models,assist clinical diagnosis,and realize precision medicine.
作者
巨妍
王嵩
JU Yan;WANG Song(Department of Radiology,Longhua Hospital,Shanghai University of Traditional Chinese Medicine,Shanghai 200032,China)
出处
《磁共振成像》
CAS
CSCD
北大核心
2023年第5期171-174,180,共5页
Chinese Journal of Magnetic Resonance Imaging
基金
上海市自然科学基金(编号:19ZR1457800)。
关键词
肠-脑轴
磁共振成像
静息态功能磁共振成像
机器学习
深度学习
gut-brain axis
magnetic resonance imaging
resting state functional magnetic resonance imaging
machine learning
deep learning
