中华中医药学刊2026，Vol.44Issue(1)：24-29,6.DOI:10.13193/j.issn.1673-7717.2026.01.005
图神经网络在中医药领域应用现状与前景展望
Current Status and Prospects of Application of Graph Neural Networks in The Field of Traditional Chinese Medicine
摘要
Abstract
With the rise and rapid development of artificial intelligence,deep learning,as an important part of the field of ar-tificial intelligence,has achieved significant results in various fields such as materials science,biomedicine,literature,and art,demonstrating high versatility and value.As an emerging deep learning method,Graph Neural Network(GNN)overcomes the lim-itation of traditional deep learning that can only be applied to Euclidean data frameworks,demonstrating its powerful ability to handle non-Euclidean complex data especially graph data,and demonstrating its enormous potential.Currently,GNN has been widely applied in the medical field and has been preliminarily applied in clinical and basic researches of traditional Chinese medi-cine.They have achieved certain results in traditional Chinese medicine prescription recommendation,symptom diagnosis and tar-get prediction of traditional Chinese medicine.By reviewing the current application status of GNN in the field of traditional Chi-nese medicine and combining the characteristics of current GNN technology,it looks forward to the future development of this technology in the field of traditional Chinese medicine.It is believed that GNN has broad application prospects in clinical diagno-sis,prescription treatment,traditional Chinese medicine research and utilization of classics.It is to provide ideas and inspiration for future research on Traditional Chinese Medicine based on graph neural networks so that traditional Chinese medicine can keep pace with the times,enhance intelligence and objectivity,and better serve the people's medical and health care and health cause of the motherland.关键词
深度学习/图神经网络/中医学Key words
deep learning/Graph Neural Network/traditional Chinese medicine分类
医药卫生引用本文复制引用
祁嘉文,刘毅..图神经网络在中医药领域应用现状与前景展望[J].中华中医药学刊,2026,44(1):24-29,6.基金项目
国家重点研发计划项目(2018YFC1704104) （2018YFC1704104）
四川省中医药管理局中医药科研专项课题重点项目(2024zd024) （2024zd024）
成都中医药大学"杏林学者"学科人才科研提升计划项目(XKTD2022014) （XKTD2022014）
