Title :
Knowledge acquisition using a fuzzy machine-learning algorithm for a knowledge-based anesthesia monitor
Author :
van den Eijkel, G.C. ; Backer, E.
Author_Institution :
Dept. of Electr. Eng., Delft Univ. of Technol., Netherlands
fDate :
31 Oct-3 Nov 1996
Abstract :
This paper discusses a new knowledge-acquisition approach for a knowledge-based anesthesia monitor. Domain knowledge was acquired by expert interviews and used by a fuzzy incremental-learning algorithm to generate rules from observations in the operating room. The rules were used to explain and detect signal patterns which indicated alarm and no-alarm situations
Keywords :
fuzzy logic; knowledge acquisition; learning (artificial intelligence); medical computing; patient monitoring; surgery; alarm situation; domain knowledge; fuzzy machine-learning algorithm; knowledge-based anesthesia monitor; no-alarm situation; operating room; signal patterns detection; surgical monitoring; Anesthesia; Condition monitoring; Fuzzy logic; Helium; Humans; Knowledge acquisition; Machine learning; Machine learning algorithms; Patient monitoring; Signal detection;
Conference_Titel :
Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE
Conference_Location :
Amsterdam
Print_ISBN :
0-7803-3811-1
DOI :
10.1109/IEMBS.1996.646387
