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題目：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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8樓: Originally posted by wanghui001 at 2013-12-18 17:50:59
現(xiàn)在收錄到第10期了，你的文章在11期，還要再等等。

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11樓: Originally posted by wanghui001 at 2014-01-02 11:55:24
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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  頁: 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.
關(guān)鍵詞
作者關(guān)鍵詞: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
通訊作者地址: Wang, YS (通訊作者)
      Liaoning Med Univ, Affiliated Hosp 1, Dept Orthoped, 5-2 Renmin St, Jinzhou 121000, Liaoning Provin, Peoples R China.
地址:
顯示增強(qiáng)組織信息的名稱 [ 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
電子郵件地址:wys200910130@163.com
出版商
ASSOC BRAS DIVULG CIENTIFICA, FACULDADE MEDICINA, SALA 21, 14049 RIBEIRAO PRETO, SAO PAULO, 00, BRAZIL
類別 / 分類
研究方向:Life Sciences & Biomedicine - Other Topics; Research & Experimental Medicine
Web of Science 類別:Biology; Medicine, Research & Experimental
文獻(xiàn)信息
文獻(xiàn)類型:Article
語種:English
入藏號: WOS:000328203500012
ISSN: 0100-879X
其他信息
IDS 號: 268XH
Web of Science 核心合集中的 "引用的參考文獻(xiàn)": 29
Web of Science 核心合集中的 "被引頻次": 0

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