Predicting the outcomes of traumatic brain injury using accurate and dynamic predictive model

Predictive models have been used widely to predict the diseases outcomes in health sector. These predictive models are emerged with new information and communication technologies. Traumatic brain injury has recognizes as a serious and crucial health problem all over the world. In order to predict br...

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Bibliographic Details
Main Authors: Alanazi, H. O. (Author), Abdullah, A. H. (Author), Qureshi, K. N. (Author), Larbani, M. (Author), Al Jumah, M. (Author)
Format: Article
Language:English
Published: Asian Research Publishing Network, 2016.
Subjects:
Online Access:Get fulltext
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042 |a dc 
100 1 0 |a Alanazi, H. O.  |e author 
700 1 0 |a Abdullah, A. H.  |e author 
700 1 0 |a Qureshi, K. N.  |e author 
700 1 0 |a Larbani, M.  |e author 
700 1 0 |a Al Jumah, M.  |e author 
245 0 0 |a Predicting the outcomes of traumatic brain injury using accurate and dynamic predictive model 
260 |b Asian Research Publishing Network,   |c 2016. 
856 |z Get fulltext  |u http://eprints.utm.my/id/eprint/71899/1/AbdulHananAbdullah2016_PredictingtheOutcomesofTraumaticBrain.pdf 
520 |a Predictive models have been used widely to predict the diseases outcomes in health sector. These predictive models are emerged with new information and communication technologies. Traumatic brain injury has recognizes as a serious and crucial health problem all over the world. In order to predict brain injuries outcomes, the predictive models are still suffered with predictive performance. In this paper, we propose a new predictive model and traumatic brain injury predictive model to improve the predictive performance to classifying the disease predictions into different categories. These proposed predictive models support to develop the traumatic brain injury predictive model. A primary dataset is constructed which is based on approved set of features by the neurologist. The results of proposed model is indicated that model has achieved the best average ranking in terms of accuracy, sensitivity and specificity. 
546 |a en 
650 0 4 |a QA75 Electronic computers. Computer science