Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Converting a rule-based expert system into a belief network

M Korver1, P J Lucas

  • 1Department of Medical Physics and Informatics, University of Amsterdam, The Netherlands.

Medical Informatics = Medecine Et Informatique
|July 1, 1993
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Neighbourhood incidence rate of paediatric dental extractions under general anaesthetic in South West England.

British dental journal·2018
Same author

Financial benefits for child health and well-being in low income or socially disadvantaged families in developed world countries.

The Cochrane database of systematic reviews·2008
Same author

The importance of size and growth in infancy: integrated findings from systematic reviews of scientific evidence and lay perspectives.

Child: care, health and development·2007
Same author

Prognostic models in medicine. AI and statistical approaches.

Methods of information in medicine·2001
Same author

A probabilistic and decision-theoretic approach to the management of infectious disease at the ICU.

Artificial intelligence in medicine·2000
Same author

Disruption of T cell homeostasis in mice expressing a T cell-specific dominant negative transforming growth factor beta II receptor.

The Journal of experimental medicine·2000
Same journal

Backpropagation and adaptive resonance theory in predicting suicidal risk.

Medical informatics = Medecine et informatique·1999
Same journal

Enhancing security and improving interoperability in healthcare information systems.

Medical informatics = Medecine et informatique·1999
Same journal

A multi-agent architecture for teaching dermatology.

Medical informatics = Medecine et informatique·1999
Same journal

A network-based training environment: a medical image processing paradigm.

Medical informatics = Medecine et informatique·1999
Same journal

Hippocrates: an integrated platform for telemedicine applications.

Medical informatics = Medecine et informatique·1999
Same journal

MEDNET97. Proceedings of a conference on the internet in medicine. November 1997.

Medical informatics = Medecine et informatique·1998
See all related articles

Converting rule-based expert systems to belief networks is challenging due to knowledge representation differences. While HEPAR

Area of Science:

  • Artificial Intelligence
  • Medical Informatics
  • Probability Theory

Background:

  • Expert systems often use heuristic methods for uncertain information.
  • Belief networks offer a mathematically sound, probability-based approach to uncertainty.

Purpose of the Study:

  • To design a belief network reformulation of the diagnostic rule-based expert system HEPAR.
  • To investigate the feasibility of converting existing rule-based expert systems to belief networks.

Main Methods:

  • Studied typical medical knowledge within the HEPAR system.
  • Analyzed differences in knowledge representation and uncertainty formalisms.
  • Mapped HEPAR objects and attributes to statistical variables for belief network construction.

Related Experiment Videos

Main Results:

  • Significant additional knowledge acquisition was necessary due to knowledge extraction challenges.
  • Differences in uncertainty formalisms hindered direct knowledge transfer.
  • HEPAR's objects, attributes, and rule conditions aided in selecting statistical variables.

Conclusions:

  • Converting rule-based expert systems like HEPAR to belief networks requires substantial knowledge engineering.
  • The structure of existing systems can guide the selection of variables for belief networks.
  • Direct conversion is complex, necessitating careful knowledge acquisition and mapping.