基金项目:安徽高校自然科学重点研究项目“疾病-基因-药物关系抽取关键技术与实证研究”(数字医学与智慧健康安徽省重点实验室KJ2019A0325);安徽省质量工程项目“计算机与程序设计”(2018mooc281);蚌埠医学院自然科学重点项目“基于词典和机器学习的基因实体识别机制研究”(BYKY1825ZD) |
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中文摘要: |
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。 |
英文摘要: |
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 and 278 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. |
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