چکیده مقاله
This paper aims to predict poor prognosis in traumatic brain injury TBI patients based on admission findings A neural network is mapped from an initial decision tree constructed from a part of data Then the designed network is trained and validated by the remained data 10 fold cross validation method is applied and the area under the ROC curve and accuracy rate are reported The most important attributes are determined from the trained network by two methods; Change of Mean of Squared Error COM and Sensitivity Analysis SA The results reveal a high accuracy rate 91 1% and significant area under the ROC curve 0 655 for the model used in this study Furthermore, the order of the important attributes in prediction which has determined by this method is accepted in clinical aspect Accordingly, the combination of different modeling method may bring out some complexities in computations and interpretations but improves the accuracy in prediction
کلیدواژهها
نویسندگان
Saeedeh Pourahmad
Biostatistics Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran,
S.Mahmoud Taheri
Faculty of Engineering Science, College of Engineering, University of Tehran, Tehran, Iran,
Iman Hafizi-Rastani
Biostatistics Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran,
Hosseinali Khalili
Shiraz Neuro Science Research Center, Department of Neuro Surgery, Shiraz University of Medical Sciences, Shiraz, Iran
شیوه ارجاع
Pourahmad, Saeedeh and Taheri, S.Mahmoud and Hafizi-Rastani, Iman and Khalili, Hosseinali and Paydar, Shahram,1394,A decision tree based neural network method for prediction of poor prognosis in traumatic brain injury patients,1st National Conference on Soft Computing,Rasht
ارائهشده در
مجموعه مقالات نخستین کنفرانس ملی محاسبات نرم27 آبان 1394 · رشت