Relation between abductive and inductive types of nursing risk management

Authors:
Akinori Abe;Hiromi Itoh Ozaku;Noriaki Kuwahara;Kiyoshi Kogure
Affiliations:
ATR Media Information Science Laboratories, Kyoto, Japan;ATR Media Information Science Laboratories, Kyoto, Japan;ATR Media Information Science Laboratories, Kyoto, Japan;ATR Media Information Science Laboratories, Kyoto, Japan
Venue:
JSAI'06 Proceedings of the 20th annual conference on New frontiers in artificial intelligence
Year:
2006

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Abstract

In this paper, we contrast inductive nursing risk management and abductive nursing risk management, point out the importance of the abductive type, and suggest cooperation between them. In general risk management, inductive management is usually adopted. If we computationally conduct inductive management, it is vital to collect a considerable number of examples to perform machine learning. For nursing risk management, risk management experts usually perform manual learning to produce textbooks. In the Accident or Incident Report Database home page, we can review various types of accidents or incidents. However, since reports are written by various nurses, the granularity and quality of reports are not sufficient for machine learning. We, therefore, explain the importance of conducting dynamic nursing risk management that can be achieved by abduction, then illustrate cooperation between abductive and inductive types of nursing risk management.