基于医疗知识库的辅助诊疗系统

发布时间：2018-03-26 01:52

本文选题：辅助诊疗　切入点：医疗知识库　出处：《计算机应用》2016年S1期

【摘要】：针对电子医疗信息日益增加而对其的组织利用率低的问题,提出了基于医疗知识库的辅助诊疗系统。首先,通过对医疗知识库中的疾病信息进行分词操作,建立倒排索引表;然后,计算输入的症状信息与相关疾病的相似度并进行排序,以作出诊断;其次,根据用户的反馈信息采用动态确定原有信息与反馈信息权重比的反馈查询方法进行优化诊断;最后,利用贝叶斯分类算法根据病例信息对进一步的检查方式作出推荐。实验结果表明,在所规定的统计策略下,初步诊断时系统的召回率达到95%,准确率达到85%,在优化诊断之后准确率达到95%。该系统以工具的形式给医疗工作者以提示,帮助提高医疗水平和质量。
[Abstract]:An auxiliary diagnosis and treatment system based on medical knowledge base is put forward in order to solve the problem that the electronic medical information is increasing and its organization utilization ratio is low. Firstly, an inverted index table is established by segmenting the disease information in the medical knowledge base. Then, the similarity between the inputted symptom information and the related diseases is calculated and sorted to make the diagnosis. Secondly, according to the feedback information of the user, the feedback query method which dynamically determines the weight ratio of the original information to the feedback information is used to optimize the diagnosis. Finally, the Bayesian classification algorithm is used to recommend the further examination methods according to the case information. The experimental results show that, under the prescribed statistical strategy, In the initial diagnosis, the recall rate of the system reached 95%, the accuracy rate reached 85%, and the accuracy rate reached 95% after the optimization of the diagnosis. The system provides medical workers with tips in the form of tools to help improve the level and quality of medical treatment.
【作者单位】：哈尔滨工业大学计算机科学与技术学院;
【基金】：国家973计划项目(2012CB316200) 国家自然科学基金资助项目(61472099,61133002) 国家科技支撑计划项目(2015BAH10F01)
【分类号】：TP18;R44

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