Development of a Bayesian Network for the prognosis of head injuries using graphical model selection techniques

被引：0
|
作者：
Sakellaropoulos, GC [1 ]
Nikiforidis, GC [1 ]
机构：
[1] Univ Patras, Sch Med, Comp Lab, GR-26500 Patras, Greece
来源：
METHODS OF INFORMATION IN MEDICINE | 1999年 / 38卷 / 01期
关键词：
Bayesian Networks; head injuries; prognosis; learning models;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The assessment of a head-injured patient's prognosis is a task that involves the evaluation of diverse sources of information. In this study we propose an analytical approach, using a Bayesian Network (BN), of combining the available evidence. The BN's structure and parameters are derived by learning techniques applied to a database (600 records) of seven clinical and laboratory findings. The BN produces quantitative estimations of the prognosis after 24 hours for head-injured patients in the outpatients department. Alternative models are compared and their performance is tested against the success rate of an expert neurosurgeon.
引用
收藏
页码：37 / 42
页数：6
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