基于BP人工神经网络模型构建电子病历系统的数据分析

背景：电子病历中包含大量能够辅助临床诊断和决策的医疗信息。 目的：利用BP人工神经网络进行电子病历的数据挖掘。 方法：针对BP人工神经网络的原理及算法进行了分析,提出BP人工神经网络模型构建的6个步骤,分别为训练数据集的确定,数据准备,网络模型的建立,进行数据挖掘,评估BP网络得到的结果及预测结果的应用。并分析了BP人工神经网络在电子病历中的相关应用。 结果与结论：利用BP人工神经网络可以对电子病历进行分析预测,查找存在的危险因素。证实BP人工神经网络在电子病历系统数据分析中具有实际应用价值。

Application of BP artificial neural network in the electronic medical record system

BACKGROUND:There are a large number of information in the electronic medical records which can assist medical diagnosis and decision-making; OBJECTIVE:To perform data mining in electronic medical records based on BP neural network. METHODS:BP artificial neural network theory and algorithms are analyzed, and there are six steps to build a BP artificial neural network model, including the training data set identification, data preparation, network model, data mining, and evaluating and predicting the results obtained from the BP network. The related applications of the BP artificial neural network in the electronic medical records were analyzed. RESULTS AND CONCLUSION:BP artificial neural network can be used to analyze and predict the electronic medical records to find the risk factors. BP artificial neural network data analysis has practical application value in the electronic medical records system.