Capturing human intelligence for modelling cognitive-based clinical decision support agents

Ali Rezaei-Yazdi*, Christopher D. Buckingham

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

The success of intelligent agents in clinical care depends on the degree to which they represent and work with human decision makers. This is particularly important in the domain of clinical risk assessment where such agents either conduct the task of risk evaluation or support human clinicians with the task. This paper provides insights into how to understand and capture the cognitive processes used by clinicians when collecting the most important data about a person’s risks. It attempts to create some theoretical foundations for developing clinically justifiable and reliable decision support systems for initial risk screening. The idea is to direct an assessor to the most informative next question depending on what has already been asked using a mixture of probabilities and heuristics. The method was tested on anonymous mental health data collected by the GRiST risk and safety tool (www.egrist.org).

Original languageEnglish
Title of host publicationArtificial Life and Intelligent Agents - Second International Symposium, ALIA 2016, Revised Selected Papers
PublisherSpringer
Pages105-116
Number of pages12
Volume732
ISBN (Print)9783319904177
DOIs
Publication statusE-pub ahead of print - 19 Apr 2018
Event2nd International Symposium on Artificial Life and Intelligent Agents, ALIA 2016 - Birmingham, United Kingdom
Duration: 14 Jun 201615 Jun 2016

Publication series

NameCommunications in Computer and Information Science
Volume732
ISSN (Print)1865-0929

Conference

Conference2nd International Symposium on Artificial Life and Intelligent Agents, ALIA 2016
CountryUnited Kingdom
CityBirmingham
Period14/06/1615/06/16

Bibliographical note

Copyright:Springer

Keywords

  • Clinical decision support systems
  • Clinical intelligence
  • Dynamic data collection
  • eHealth
  • Healthcare
  • Intelligent agents
  • Risk assessment

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  • Cite this

    Rezaei-Yazdi, A., & Buckingham, C. D. (2018). Capturing human intelligence for modelling cognitive-based clinical decision support agents. In Artificial Life and Intelligent Agents - Second International Symposium, ALIA 2016, Revised Selected Papers (Vol. 732, pp. 105-116). (Communications in Computer and Information Science; Vol. 732). Springer. https://doi.org/10.1007/978-3-319-90418-4_9