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

页码：37 / 42

页数：6

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