BP神经网络在疾病分析影响因素中的作用

背景:疾病产生原因复杂多样,临床医生对大量样本病历数据挖掘的探讨往往缺乏有效的手段,信息技术的应用能力有待提高.目的:利用人工神经网络的BP算法,对临床大样本量的病历进行分析,以找出某种疾病的致病因素与疾病本身之间的内在关系.方法:以高血压病为例,以某中医院2010-07的高血压患者病历数据为实验数据,对疾病的影响因素进行建模,优选 Microsoft SQL Server 2005 Analysis Services智能工具,分析其挖掘结果,并利用单独查询进行预测与决策支持.结果与结论:应用基于BP算法的人工神经网络分析疾病的致病因素对疾病本身的影响有较好的预测效果,有利于提升医务人员借助信息技术方法在临床诊断的水平,提高疾病诊断效率.

Abstract：

BACKGROUND: Disease pathogenic factors are complicated. There is not an effective method to analyze large sample data mining, and application ability of information technology of clinical doctors needs to be improved. OBJECTIVE: Using BP algorithm of artificial neural network to analyze large sample clinical cases, in order to explore inner relations between disease pathogenic factors and diseases.METHODS: Take hypertension for example, medical data of patients with hypertension in a traditional Chinese medical hospital served as experimental data, and the influence factors of the disease were simulated with Microsoft SQL Server 2005 Analysis Services, the mining data was analyzed, and a single query was used as prediction and decision support.RESULTS AND CONCLUSION: Analysis of effect of disease pathogenic factors on disease itself based on artificial neural network with BP algorithm has good predictive effect in clinical diagnosis, which is of benefit to enhance the diagnostic efficiency of medical personnel using information technology.

BP neural network in analysis of disease influential factors

BACKGROUND: Disease pathogenic factors are complicated. There is not an effective method to analyze large sample data mining, and application ability of information technology of clinical doctors needs to be improved. OBJECTIVE: Using BP algorithm of artificial neural network to analyze large sample clinical cases, in order to explore inner relations between disease pathogenic factors and diseases.METHODS: Take hypertension for example, medical data of patients with hypertension in a traditional Chinese medical hospital served as experimental data, and the influence factors of the disease were simulated with Microsoft SQL Server 2005 Analysis Services, the mining data was analyzed, and a single query was used as prediction and decision support.RESULTS AND CONCLUSION: Analysis of effect of disease pathogenic factors on disease itself based on artificial neural network with BP algorithm has good predictive effect in clinical diagnosis, which is of benefit to enhance the diagnostic efficiency of medical personnel using information technology.