Imprecise Meanings as a Cause of Uncertainty in Medical Knowledge-Based Systems

TL;DR

This paper highlights how lexical imprecision causes uncertainty in medical knowledge-based systems, affecting inference and user interaction, and proposes techniques to address this issue.

Contribution

It introduces the concept of lexical imprecision as a source of uncertainty and suggests methods to mitigate its impact on knowledge-based systems.

Findings

Lexical imprecision can degrade system performance

It causes difficulties in user interface and inference processes

Proposed techniques can help handle lexical imprecision

Abstract

There has been a considerable amount of work on uncertainty in knowledge-based systems. This work has generally been concerned with uncertainty arising from the strength of inferences and the weight of evidence. In this paper we discuss another type of uncertainty: that which is due to imprecision in the underlying primitives used to represent the knowledge of the system. In particular, a given word may denote many similar but not identical entities. Such words are said to be lexically imprecise. Lexical imprecision has caused widespread problems in many areas. Unless this phenomenon is recognized and appropriately handled, it can degrade the performance of knowledge-based systems. In particular, it can lead to difficulties with the user interface, and with the inferencing processes of these systems. Some techniques are suggested for coping with this phenomenon.