DocumentCode :
617736
Title :
On the use of the incremental support vector machines for monitoring systems in intensive care unit
Author :
Ben Rejab, Fahmi ; Nouira, Kaouther ; Trabelsi, Amine
Author_Institution :
Inst. Super. de Gestion de Tunis, Univ. de Tunis, Le Bardo, Tunisia
fYear :
2013
fDate :
9-11 May 2013
Firstpage :
266
Lastpage :
270
Abstract :
This paper intends to propose an on-line monitoring system based on the incremental support vector machines (LASVM). In fact, the current monitoring system in ICU presents a real threat for the patient life due to the high rate of false or non significant alarms. In this paper we aim to improve the current system by applying an intelligent and on-line classification method (the LASVM). This method adds new instances of medical parameters of patients over time and deals with large amount of data streams in ICU. Besides, the LASVM generates an optimal model of prediction which provides a better and correct description of the different patients´ states over time. All obtained results of the LASVM on real-medical databases prove the performance of this new system. Our proposal reduces the false alarms and conserves the high level of sensitivity compared to the standard SVM and the current system.
Keywords :
database management systems; patient care; patient monitoring; support vector machines; LASVM; incremental support vector machines; intensive care unit; on-line classification method; on-line monitoring system; real-medical databases; Arteries; Biomedical monitoring; Bismuth; Databases; Monitoring; Performance evaluation; Support vector machine classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE), 2013 International Conference on
Conference_Location :
Konya
Print_ISBN :
978-1-4673-5612-1
Type :
conf
DOI :
10.1109/TAEECE.2013.6557283
Filename :
6557283
Link To Document :
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