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

Automated integration of external databases: a knowledge-based approach to enhancing rule-based expert systems.

L Berman1, M R Cullen, P L Miller

  • 1Center for Medical Informatics, Yale University School of Medicine, New Haven, CT 06510.

Proceedings. Symposium on Computer Applications in Medical Care
|January 1, 1992
PubMed
Summary

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

Structural biology at the National Synchrotron Light Source II.

Journal of synchrotron radiation·2025
Same author

Surgical site infections in neonates are independently associated with longer hospitalizations.

Journal of perinatology : official journal of the California Perinatal Association·2017
Same author

Functional outcomes of conservatively managed acute ruptures of the Achilles tendon.

The bone & joint journal·2017
Same author

Cross-national comparisons of increasing suicidal mortality rates for Koreans in the Republic of Korea and Korean Americans in the USA, 2003-2012.

Epidemiology and psychiatric sciences·2016
Same author

Medical Informatics Training at Yale University School of Medicine.

Yearbook of medical informatics·2016
Same author

Hearing conservation in the primary aluminium industry.

Occupational medicine (Oxford, England)·2015

This study introduces an automated method for expanding biomedical expert systems by integrating external online databases. The DBX system enhances knowledge bases for better decision support and information retrieval.

Area of Science:

  • Biomedical Informatics
  • Artificial Intelligence
  • Knowledge Representation

Background:

  • Expert systems in biomedicine face challenges in knowledge base maintenance and expansion.
  • Integrating diverse data sources is crucial for enhancing expert system capabilities.

Purpose of the Study:

  • To present a novel knowledge-based method for automatic knowledge base augmentation in biomedical expert systems.
  • To introduce the DBX prototype system designed for this purpose.

Main Methods:

  • Developed a method for automatically integrating data from external, commercial online databases with existing expert system knowledge bases.
  • Built a prototype system named DBX to implement this integration technique.

Main Results:

Related Experiment Videos

  • The DBX system successfully augments expert system knowledge bases.
  • Demonstrated the utility of DBX as a decision support aid and bibliographic retrieval tool.

Conclusions:

  • Automated knowledge base augmentation is feasible and beneficial for biomedical expert systems.
  • The DBX system offers a practical solution for enhancing expert system knowledge and utility.