口腔门诊病历质量控制算法的研究  

Research on Algorithm for Quality Control of Dental Outpatient Medical Records

作　　者：车林彬 陈杰 Che Linbin;Chen Jie(Shenzhen Stomatological Hospital of Southern Medical University,Shenzhen 518118,China;School of Computer and Software,Shenzhen University,Shenzhen 518061,China)

机构地区：[1]南方医科大学深圳口腔医院(坪山),深圳518118 [2]深圳大学计算机与软件学院,深圳518061

出　　处：《现代科学仪器》2024年第2期214-218,共5页Modern Scientific Instruments

基　　金：国家重点研发计划项目(编号:2020YFA0908700)。

摘　　要：口腔门诊病历数据分类可有效提高医疗卫生服务和病历质量控制水平,使医师的工作更加高效。为解决口腔门诊病历数据的分类问题及病历质量控制效率低等问题,本文提出了一种构建变基宽神经网络模型的算法。首先,采用流形分析方法,对牙科医生的医疗记录进行分类。并利用指标化的方法对相似性矩阵进行修正,同时收集使用伤口敷料治疗口腔患者的数据作为测试数据,并比较了分类的准确性、收敛时间、分类精度。实验结果表明,径向基函数神经网络分类算法的分类准确度为98%,且平均分类精度比其他方法高5%以上,该算法可以提高口腔门诊病历数据样本集的分类精度和收敛速度,提高病历质量控制效率。The classification of dental outpatient medical record data can effectively improve the level of medical and health services and quality control of medical records,making the work of physicians more efficient.To solve the classification problem of dental outpatient medical record data and the low efficiency of medical record quality control,this paper proposes an algorithm for constructing a variable basis width neural network model.Firstly,manifold analysis method is used to classify the medical records of dentists.And the similarity matrix was modified using an indexing method,while data from oral patients treated with wound dressings were collected as test data.The accuracy,convergence time,and classification accuracy were compared.The experimental results show that the classification accuracy of the Radial basis function neural network classification algorithm is 98%,and the average classification accuracy is more than 5%higher than other methods.The algorithm can improve the classification accuracy and Rate of convergence of the dental outpatient medical record data sample set,and improve the quality control efficiency of medical records.

关 键 词：口腔 门诊病历 质量控制 算法 

分 类 号：G449[哲学宗教—心理学]