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题目：Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China.
作者：Shi L, Wang XC, Wang YS.
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Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China
作者:Shi, L (Shi, L.)[ 1 ] ; Wang, XC (Wang, X. C.)[ 1 ] ; Wang, YS (Wang, Y. S.)[ 2 ]
BRAZILIAN JOURNAL OF MEDICAL AND BIOLOGICAL RESEARCH
卷: 46  期: 11  页: 993-999
DOI: 10.1590/1414-431X20132948
出版年: NOV 2013
查看期刊信息
摘要
The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regression models. The ANN model was tested against actual outcomes of an intertrochanteric femoral fracture database in China. The ANN model was generated with eight clinical inputs and a single output. ANN's performance was compared with a logistic regression model created with the same inputs in terms of accuracy, sensitivity, specificity, and discriminability. The study population was composed of 2150 patients (679 males and 1471 females): 1432 in the training group and 718 new patients in the testing group. The ANN model that had eight neurons in the hidden layer had the highest accuracies among the four ANN models: 92.46 and 85.79% in both training and testing datasets, respectively. The areas under the receiver operating characteristic curves of the automatically selected ANN model for both datasets were 0.901 (95%CI=0.814-0.988) and 0.869 (95%CI=0.748-0.990), higher than the 0.745 (95%CI=0.612-0.879) and 0.728 (95%CI=0.595-0.862) of the logistic regression model. The ANN model can be used for predicting 1-year mortality in elderly patients with intertrochanteric fractures. It outperformed a logistic regression on multiple performance measures when given the same variables.
关键词
作者关键词:Artificial neural network; Intertrochanteric fracture; Outcome prediction; One-year mortality
KeyWords Plus:HIP FRACTURE; LOGISTIC-REGRESSION; SURGERY; METAANALYSIS; INJURY; LEVEL; TREES
作者信息
通讯作者地址: Wang, YS (通讯作者)
      Liaoning Med Univ, Affiliated Hosp 1, Dept Orthoped, 5-2 Renmin St, Jinzhou 121000, Liaoning Provin, Peoples R China.
地址:
显示增强组织信息的名称 [ 1 ] Dalian Maritime Univ, Informat Sci & Technol Coll, Dalian, Peoples R China
      [ 2 ] Liaoning Med Univ, Affiliated Hosp 1, Dept Orthoped, Jinzhou 121000, Liaoning Provin, Peoples R China
电子邮件地址:wys200910130@163.com
出版商
ASSOC BRAS DIVULG CIENTIFICA, FACULDADE MEDICINA, SALA 21, 14049 RIBEIRAO PRETO, SAO PAULO, 00, BRAZIL
类别 / 分类
研究方向:Life Sciences & Biomedicine - Other Topics; Research & Experimental Medicine
Web of Science 类别:Biology; Medicine, Research & Experimental
文献信息
文献类型:Article
语种:English
入藏号: WOS:000328203500012
ISSN: 0100-879X
其他信息
IDS 号: 268XH
Web of Science 核心合集中的 "引用的参考文献": 29
Web of Science 核心合集中的 "被引频次": 0

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