Differences in the identification of anomalies from computerized physiological data

Moss, L. , Sleeman, D. and Kinsella, J. (2012) Differences in the identification of anomalies from computerized physiological data. K-MED 2012 - International Workshop on Capturing and Refining Knowledge in the Medical Domain, Galway City, Ireland, 08-12 Oct 2012. pp. 11-21.

Abstract

To develop knowledge bases for use in knowledge-based (or expert) systems, domain experts are often interviewed or are asked to perform knowledge acquisition tasks. Although domain experts are highly regarded, they can still display cognitive biases (i.e. errors in judgement, knowledge, and reasoning) which can affect their performance and lead to differences in both the way several domain experts perform the task, and in some cases the conclusions drawn. Consequently, developing accurate knowledge bases is still a challenge for knowledge engineers. In this paper we illustrate this challenge with a case study from the Intensive Care Unit (ICU) domain. In this task the ICU clinicians were asked to identify possible anomalies from a set of patient datasets. In total, the clinicians identified 83 anomalies, of which there were only 9 instances where an anomaly was identified by more than one clinician. A further investigation explores whether individual problem solving strategies or biases are possibly responsible for the differences.

• Item Type: Conference or Workshop Item
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Kinsella, Professor John and Moss, Dr Laura
• Authors: Moss, L., Sleeman, D., and Kinsella, J.
• Subjects: R Medicine > R Medicine (General)
• College/School: College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing
• Journal Name: Proceedings of the First International Workshop on Capturing and Refining Knowledge in the Medical Domain