[1]田娟,朱姝婧,陆强,等.基于BP神经网络预测儿童甲状腺疾病的模型研究[J].中国医学物理学杂志,2020,37(10):1340-1344.[doi:DOI:10.3969/j.issn.1005-202X.2020.10.022]
　TIAN Juan,ZHU Shujing,LU Qiang,et al.Prediction model of pediatric thyroid disease based on back-propagation neural network[J].Chinese Journal of Medical Physics,2020,37(10):1340-1344.[doi:DOI:10.3969/j.issn.1005-202X.2020.10.022]
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基于BP神经网络预测儿童甲状腺疾病的模型研究()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
37
期数:
2020年第10期
页码:
1340-1344
栏目:
医学人工智能
出版日期:
2020-10-29

文章信息/Info

Title:
Prediction model of pediatric thyroid disease based on back-propagation neural network
文章编号:
1005-202X（2020）10-1340-05
作者:
田娟1; 朱姝婧2; 陆强1; 李坤1; 张西学1
1.山东第一医科大学医学信息工程学院， 山东 泰安 271016； 2.泰安市疾病预防控制中心检验科， 山东 泰安 271016
Author(s):
TIAN Juan1;  ZHU Shujing2;  LU Qiang1;  LI Kun1;  ZHANG Xixue1
1. School of Medical Information Engineering, Shandong First Medical University, Taian 271016, China 2. Department of Laboratory, Taian Center for Diseases Prevention and Control, Taian 271016, China
关键词:
儿童甲状腺疾病; BP神经网络; 疾病预测; 分类正确率
Keywords:
Keywords: pediatric thyroid disease back-propagation neural network disease prediction classification accuracy
分类号:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2020.10.022
文献标志码:
A
摘要:
目的：构建儿童甲状腺疾病的预测模型。方法：根据某市疾病预防控制中心2013年~2016年采集的1 400名8~11岁儿童的体检数据及临床初步诊断结果作为研究数据，随机抽取其中的1 000名儿童作为训练样本，剩余的400名儿童作为测试样本，利用 MATLAB R2018b软件编程实现三层BP神经网络模型。结果：当选择log&log组合作为隐含层和输出层的传递函数，隐含层节点数目选择8时，模型的分类正确率达到91.43%。结论：BP神经网络应用于儿童甲状腺疾病的预测，可以为疾病的防治工作提供理论依据。
Abstract:
Abstract: Objective To construct a prediction model of thyroid disease in pediatric patients. Methods The physical examination data and preliminary clinical diagnoses of 1 400 children aged 8-11 years were collected from 2013 to 2016 in a Center for Disease Prevention and Control. One thousand out of 1 400 children were randomly selected as training samples, and the remaining 400 were used as test samples. A three-layer back-propagation neural network model was constructed by MATLAB R2018b software. Results The classification accuracy of the model reached 91.43% when the combination of log&log was selected as the transfer function of the hidden layer and the output layer, with 8 nodes in the hidden layer. Conclusion Back-propagation neural network can be applied to the prediction of thyroid diseases in children, and provide a theoretical basis for the prevention and treatment of diseases.

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备注/Memo

备注/Memo:
【收稿日期】2020-04-11 【基金项目】泰安市科技发展计划（201730338） 【作者简介】田娟，讲师，硕士，研究方向：智能控制和模式识别，E-mail: jtian@sdfmu.edu.cn
更新日期/Last Update: 2020-10-29