Paper Info
Title
Automatic planning of treatment of infants with respiratory failure through rough set modeling
Abstract
We discuss an application of rough set tools for modeling networks of classifiers induced from data and ontology of concepts delivered by experts. Such networks allow us to develop strategies for automated planning of a treatment of infants with respiratory illness. We report results of experiments with the networks of classifiers used in automated planning of the treatment of newborn infants with respiratory failure. The reported experiments were performed on medical data obtained from the Neonatal Intensive Care Unit in the Department of Pediatrics, Collegium Medicum, Jagiellonian University.
Year
DOI
Venue
2006
10.1007/11908029_44
RSCTC
Keywords
Field
DocType
collegium medicum,rough set tool,respiratory failure,automated planning,neonatal intensive care unit,reported experiment,jagiellonian university,rough set modeling,automatic planning,newborn infant,respiratory illness,medical data,rough set
Intensive care unit,Ontology,Neonatal intensive care unit,Rough set,Artificial intelligence,Medical emergency,Respiratory failure,Medicine
Conference
Volume
ISSN
ISBN
4259
0302-9743
3-540-47693-8
Citations 
PageRank 
References 
16
0.64
6
Authors
5
Name
Order
Citations
PageRank
Jan G. Bazan1160.64
Piotr Kruczek2243.26
Stanislawa Bazan-Socha3385.32
Andrzej Skowron45062421.31
Jacek J. Pietrzyk5241.57