Mining clinical data: Selecting decision support algorithm for the MET-AP system

被引：0
|
作者：
Blaszczynski, J
Farion, K
Michalowski, W
Wilk, S
Rubin, S
Weiss, D
机构：
[1] Poznan Univ Tech, Inst Comp Sci, PL-60965 Poznan, Poland
[2] Childrens Hosp Eastern Ontario, Ottawa, ON K1H 8L1, Canada
[3] Univ Ottawa, Sch Management, Ottawa, ON K1N 6N5, Canada
来源：
ARTIFICIAL INTELLIGENCE IN MEDICINE, PROCEEDINGS | 2005年 / 3581卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We have developed an algorithm for triaging acute pediatric abdominal pain in the Emergency Department using the discovery-driven approach. This algorithm is embedded into the MET-AP (Mobile Emergency Triage - Abdominal Pain) system - a clinical decision support system that assists physicians in making emergency triage decisions. In this paper we describe experimental evaluation of several data mining methods (inductive learning, case-based reasoning and Bayesian reasoning) and results leading to the selection of the rule-based algorithm.
引用
收藏
页码：429 / 433
页数：5
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