【摘要】 目的:挖掘针灸相关疾病、基因和药物间的新关联。方法:提出一种基于SVM的机器学习算法,结合词典识别疾病、基因和药物实体并挖掘三者之间的关联,构建针灸相关疾病、基因和药物关联网络。结果:识别出针灸相关的296种疾病、51种基因和278种药物,并在27种疾病、13种基因和135种药物之间挖掘出704种关联,构建3个关联网络,发现了262种新关联。结论:针灸相关疾病-基因-药物之间存在大量程度不一的关联,为针灸精准医疗提供了新的研究思路。更多还原

【Abstract】 Objective To mine the new associations in acupuncture-related diseases,genes and drugs. Methods A support vector machine( SVM)-based machine learning algorithm was proposed and different association networks for acupuncture-related diseases,genes and drugs were established by identifying the diseases,genes and drugs with dictionaries and mining their associations. Results A total of 296 acupuncture-related diseases,51 genes and278 drugs were identified,and 704 associations were mined in 27 diseases,13 genes and 135 drugs. Three association networks were established,which discovered a total of 262 new associations in acupuncture-related diseases,genes and drugs. Conclusion New associations are detected in acupuncture-related diseases,genes and drugs,which can thus provide certain new ideas for studying the precision treatment of diseases by acupuncture.更多还原