首页> 美国卫生研究院文献>Open Medicine >Comparative Study of Back Propagation Artificial Neural Networks and Logistic Regression Model in Predicting Poor Prognosis after Acute Ischemic Stroke

【2h】

Comparative Study of Back Propagation Artificial Neural Networks and Logistic Regression Model in Predicting Poor Prognosis after Acute Ischemic Stroke

机译：反向传播人工神经网络和Logistic回归模型预测急性缺血性中风预后不良的比较研究

代理获取

本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。

页面导航

摘要
著录项
相似文献
相关主题

摘要

ObjectiveTo investigate the predictive value of clinical variables on the poor prognosis at 90-day follow-up from acute stroke onset, and compare the diagnostic performance between back propagation artificial neural networks (BP ANNs) and Logistic regression (LR) models in predicting the prognosis.

机译：目的探讨临床变量对急性卒中发作90天后不良预后的预测价值，并比较反向传播人工神经网络（BP ANN）和Logistic回归（LR）模型在预测预后中的诊断性能。

著录项

期刊名称 Open Medicine
作者
Yaru Liang; Qiguang Li; Peisong Chen; Lingqing Xu; Jiehua Li;
展开▼
作者单位

展开▼
年(卷),期 2019(14),-1
年度 2019
页码 324–330
总页数 7
原文格式 PDF
正文语种
中图分类药学;
关键词
Back propagation artificial neural networks Logistic regression model Acute ischemic stroke Poor outcome Clinical variables;

机译：反向传播人工神经网络;Logistic回归模型;急性缺血性卒中;不良预后;临床变量;

相似文献

外文文献
中文文献
专利

1. Comparative study of back propagation artificial neural networks and logistic regression model in predicting poor prognosis after acute ischemic stroke [J] . Yaru Liang, Qiguang Li, Peisong Chen, Open medicine . 2019,第1期

机译：反向传播人工神经网络与Logistic回归模型预测急性缺血性卒中后不良预后的比较研究
2. Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree [J] . Dieu Tien Bui, Tran Anh Tuan, Klempe Harald, Landslides . 2016,第2期

机译：浅层滑坡灾害的空间预测模型：支持向量机，人工神经网络，核逻辑回归和逻辑模型树的有效性的比较评估
3. Predicting Risk of Acute Appendicitis: A Comparison of Artificial Neural Network and Logistic Regression Models [J] . Leila Shahmoradi, Reza Safdari, Mir Mikail Mirhosseini, Acta medica Iranica. . 2018,第12期

机译：预测急性阑尾炎的风险：人工神经网络和Logistic回归模型的比较
4. Application of Conditional Logistic Regression method in a prospective effectiveness comparative study among patients with Acute Ischemic Stroke [C] . Cai Jianxiong, Zhao Yuanqi, Guo Xianping, 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops . 2011

机译：条件对数回归方法在急性缺血性卒中患者前瞻性疗效比较研究中的应用
5. A comparative analysis of artificial neural networks, classification trees, and multivariate linear regression for predicting retail employee tenure and turnover [D] . Ostberg, David Edward 2005

机译：人工神经网络，分类树和多元线性回归的比较分析，用于预测零售雇员的任期和营业额
6. Multivariable Logistic Regression And Back Propagation Artificial Neural Network To Predict Diabetic Retinopathy [O] . Litong Yao, Yifan Zhong, Jingyang Wu, 2019

机译：多变量Logistic回归和反向传播人工神经网络预测糖尿病性视网膜病变
7. Comparative study of back propagation artificial neural networks and logistic regression model in predicting poor prognosis after acute ischemic stroke [O] . Yaru Liang, Qiguang Li, Peisong Chen, 2019

机译：背部繁殖人工神经网络与逻辑回归模型预测急性缺血性卒中后预测的比较研究
8. Modeling Small Unmanned Aerial System Mishaps Using Logistic Regression and Artificial Neural Networks. [R] . Wolf, S. E. 2012

机译：利用Logistic回归和人工神经网络建模小型无人机系统事故。

Comparative Study of Back Propagation Artificial Neural Networks and Logistic Regression Model in Predicting Poor Prognosis after Acute Ischemic Stroke

摘要

著录项

相似文献

相关主题

期刊订阅