首页> 外文会议>Machine Learning and Applications, 2009. ICMLA '09 >Artificial Neural Networks Prognostic Evaluation of Post-Surgery Complications in Patients Underwent to Coronary Artery Bypass Graft Surgery
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Artificial Neural Networks Prognostic Evaluation of Post-Surgery Complications in Patients Underwent to Coronary Artery Bypass Graft Surgery

机译:人工神经网络对冠状动脉搭桥手术患者术后并发症的预后评估

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In this paper we explore the applications of artificial neural networks in the field of heart surgery, more specifically in the prognostic evaluation of post-surgery complications, such as death, reintubation, prolonged mechanical ventilation and the need for extracorporeal circulation in patients who underwent coronary artery bypass graft surgery. Predictive variables were limited to information available before the procedure, and outcome variables were represented only by events that occurred postoperatively. We also employed the principal component analysis technique to further reduce the complexity of our input data set in an attempt to improve artificial neural network efficiency and reliability
机译:在本文中,我们探讨了人工神经网络在心脏外科领域的应用,尤其是在评估术后并发症(例如死亡,重新插管,长时间的机械通气以及接受冠状动脉患者的体外循环)的预后评估中动脉搭桥术。预测变量仅限于术前可获得的信息,而结果变量仅由术后发生的事件代​​表。我们还采用主成分分析技术进一步降低了输入数据集的复杂度,以尝试提高人工神经网络的效率和可靠性

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