Knowledge acquisition using a fuzzy machine-learning algorithm for a knowledge-based anesthesia monitor

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.