| 基于特征选择和神经网络的糖尿病预测模型研究 |
| 修订日期：2022-11-19 点此下载全文 |
| 引用本文：宁莉燕,陈建荣,董建成,等.基于特征选择和神经网络的糖尿病预测模型研究[J].医学信息学杂志,2023,44(2):47-51 |
| 摘要点击次数: |
| 全文下载次数: |
|
| 基金项目:江苏省医院协会医院管理创新研究课题“医联体背景下基于特征选择的糖尿病辅助诊断模型研究”(项目编号:JSYGY-3-2021-421)；南通市科技计划项目指令性课题“医联体背景下基于边缘计算的糖尿病辅助诊疗预测模型关键技术研究”(项目编号:JC2020045)；南通市科技计划项目“基于大数据的糖尿病队列数据库建立及预测模型构建研究”(项目编号:JC2022155) 。 |
|
| 中文摘要:采用特征选择算法和人工神经网络建立糖尿病预测模型,阐述模型构建及评价步骤、方法。以灵敏度、特异度、准确率、ROC-AUC为指标评估模型的预测性能,并与其他算法模型进行对比分析,实验结果表明基于特征选择和人工神经网络的糖尿病预测模型对临床指标未知且复杂的数据集具有更好的抗干扰能力和预测性能。 |
| 中文关键词:糖尿病预测 特征选择 参数优化 神经网络 |
| |
| Study on Diabetes Prediction Model Based on Feature Selection and Neural Network |
|
|
| Abstract:A diabetes prediction model is constructed based on feature selection algorithm and artificial neural network, and the steps and methods of model construction and evaluation are expounded. Sensitivity, specificity, accuracy and ROC-AUC are used as evaluation metrics to evaluate the performance of the proposed model, and the proposed model is compared with other algorithms through experiments. The result indicates that the diabetes prediction model based on feature selection and artificial neural network has better anti-interference capability and predictive performance, which is more suitable for complex datasets with unknown influencing indicators. |
| keywords:diabetes prediction feature selection parameter optimization neural network |
| 查看全文 查看/发表评论 下载PDF阅读器 |
