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基于协同过滤算法的中医智能问诊系统研究 被引量:17

Research on Intelligent Chinese Medical Consultation System Based on Collaborative Filtering Algorithm
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摘要 目的研究中医智能问诊系统,实现快速获取关键症状并完成辨证,为中医问诊智能化、客观化提供了一种新的思路和方法。方法采用基于物品的协同过滤推荐算法(Item-Based Collaborative Filtering,ItemCF)和遗传算法构建症状获取模块以获取患者的症状,利用随机森林算法构建分类器并基于获取到的症状完成中医辨证。结果该系统实现了高效地获取患者症状并完成中医辨证。在13次提问次数下,便能获得辨证所需的核心症状,实现证候分类器90%以上的辨证效果。结论该问诊系统能够较好地解决中医问诊中"问什么、怎么问"的两个核心问题,相比依据问诊量表获取症状,极大地简化了问诊中关键症状获取的过程,并能够在证候分类中保持较好的分类效果,在问诊客观化研究上具有一定的实用价值。 Objective To study the intelligent diagnosis system of traditional Chinese medicine(TCM), realize the rapid acquisition of key symptoms and complete syndrome differentiation, and provide a new way of thinking and method for the intellectualization and objectification of TCM diagnosis. Methods The item-based collaborative filtering(ItemCF)and genetic algorithm were used to construct the symptom acquisition module to obtain the symptoms of patients. The random forest algorithm was used to construct the classifier and complete the syndrome differentiation based on the acquired symptoms. Results The system can effectively obtain the symptoms of patients and complete TCM syndrome differentiation. The system can obtain the core symptoms needed for syndrome differentiation and achieve the syndrome differentiation effect of more than 90% of the syndrome classifiers under 13 inquiries. Conclusion The experimental results show that the inquiry system can better solve the two core problems of"what to ask and how to ask"in the TCM inquiry. Compared with obtaining symptoms according to the inquiry scale, it greatly simplifies the process of symptom acquisition in the inquiry and can maintain a better classification effect in the syndrome classification. This research provides a new idea and method for the intellectualization of TCM inquiry, and has a certain practical value in the objectification research of inquiry, and has a certain practical value in the objectification research of inquiry.
作者 迪盼祺 夏春明 王忆勤 高慧 许朝霞 Di Panqi;Xia Chunming;Wang Yiqin;Gao Hui;Xu Zhaoxia(School of Mechanical and Power Engineering,East China University of Science and Technology,Shanghai 200237,China;School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science,Shanghai 201620,China;Comprehensive Laboratory of Four Diagnostic Methods,Shanghai University of Traditional Chinese Medicine,Shanghai 201203,China)
出处 《世界科学技术-中医药现代化》 CSCD 北大核心 2021年第1期247-255,共9页 Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology
基金 国家自然科学基金委员会面上项目(81673880):基于中医四诊大数据的冠心病风险评估与预测模型研究,负责人:王忆勤 上海市科学技术委员会科研计划项目(No.13DZ2261000):上海市健康辨识与评估重点实验室,负责人:王忆勤 上海市卫生和计划生育委员会中医药科技创新项目(ZYKC201701017):冠心病风险预测及中医健康管理系统的研制,负责人:许朝霞。
关键词 中医问诊 ItemCF 遗传算法 证候分类 TCM inquiry ItemCF Genetic algorithm Syndrome classification
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