Prognostic performance of two expert systems based on Bayesian belief networks
Prognostic performance of two expert systems based on Bayesian belief networks
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DOI：
10.1016/s0167-9236(99)00059-7
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发表时间：
2000-01-01
影响因子：
7.5
通讯作者：
Nikiforidis, GC
中科院分区：
文献类型：
--
作者：
Sakellaropoulos, GC;Nikiforidis, GC
基于贝叶斯信念网络，建立了一个脑外伤患者24 h预后的决策支持系统，该系统采用模型选择方法，应用于包含7个临床和实验室变量的数据库（637例）。它的性能与其他系统进行了比较，包括一个更简单的信念网络，假设结果之间的条件独立性，以及一个人类专家。结果表明，它的性能是没有显着不同的神经外科医生的专家，并优于独立模型的性能。因此，非神经外科ICU临床医生的预后判断可以通过使用该系统来帮助。(C)2000 Elsevier Science B.V.保留所有权利。
A decision support system for the prognosis at 24 h of head-injured patients of the intensive care unit (ICU), based on Bayesian belief networks, is constructed by model selection methods applied to a database (637 cases) of seven clinical and laboratory variables. Its performance is compared to other systems, including a simpler belief network that assumes conditional independence among the findings, and a human expert. Results indicate that its performance is not significantly different than that of the neurosurgeon expert and better than the performance of the independence model. Thus, the prognostic judgment of non-neurosurgeon ICU clinicians can be aided by the use of this system. (C) 2000 Elsevier Science B.V. All rights reserved.