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首页> 外文期刊>American Journal of Health Research >Predicting patient outcomes via neural network estimation of discharge APACHE scores for traumatic brain injury
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Predicting patient outcomes via neural network estimation of discharge APACHE scores for traumatic brain injury

机译：通过神经网络估计脑外伤的出院APACHE评分预测患者结果

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It is highly desirable to be able to predict the likely outcome of critical patients admitted to the intensive care unit (ICU) for traumatic brain injury (TBI). Vital signs, laboratory values, and clinical assessments from throughout a patient's ICU stay were collected retrospectively in an IRB-approved protocol from a Level I Trauma-Military Medical Center in the Southwest. ICU patients were included if they had been admitted for TBI during a five-year period ending in October 2007. Data were collected for 139 ICU patients with TBI. Admission and discharge APACHE IV scores were then derived from the collected data for each patient. A static back propagation neural network was developed to predict a patient's ICU outcome vis-a-vis discharge APACHE IV scores. The resulting network, trained using leave-one-out methodology, was able to predict the discharge APACHE score on average within 12.9% of the actual score.
机译：非常需要能够预测因重度脑损伤（TBI）而进入重症监护病房（ICU）的重症患者的可能结局。在IRB批准的方案中，从西南I级创伤军事医学中心回顾性收集了患者在ICU整个住院期间的生命体征，实验室值和临床评估。如果在截至2007年10月的5年中被收治为TBI，则包括ICU患者。收集了139位ICU TBI患者的数据。然后从收集的每位患者数据中得出入院和出院APACHE IV评分。开发了静态反向传播神经网络来预测患者的ICU结局与出院APACHE IV评分之间的关​​系。使用留一法进行训练的结果网络能够在平均实际分数的12.9％范围内预测出院APACHE分数。

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