@INPROCEEDINGS { Rsds2194,
author = {Rubin, Steven and Wilk, Szymon and Slowinski, Roman and Michalowski, Wojtek and Farion, Ken}, 
title = {Rough Set Methodology in Clinical Practice: Controlled Hospital Trial of the MET System}, 
booktitle = {Rough Sets and Current Trends in Computing}, 
conference = {Rough Sets and Current Trends in Computing}, 
series =  = {Lecture Notes in Artificial Intelligence}, 
volume = 3066, 
pages = {805-814}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
month = {June}, 
year = 2004, 
editor = {Tsumoto, Shusaku and Slowinski, Roman W. and Komorowski, Jan and Grzymala-Busse, Jerzy W.}, 
issn = {0302-9743}, 
isbn = {3-540-22117-4}, 
abstract = {Acute abdominal pain in childhood is a common but diag-nostically challenging problem facing Emergency Department personnel. Experienced physicians use a combination of key clinical attributes to assess and triage a child, but residents and inexperienced physicians may lack this ability. In order to assist them, we used knowledge discovery techniques based on rough set theory to develop a clinical decision model to support the triage. The model was implemented as a module for the Mobile Emergency Triage system - a clinical decision support system for the rapid emergency triage of children with acute pain. The abdominal pain module underwent a clinical trial in the Emergency Department of a teaching hospital. The trial allowed us to compare in a prospective manner the accuracy of the system to the triage performance of the physicians and the residents. The preliminary results are very encouraging and they demonstrate validity of developing computer-based support tools for a clinical triage.}, 
keywords = {rough set theory (RST), emergency triage, clinical trial, clinical decision support systems, handheld computers, }, 
}