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

An expert diagnostic program for dermatology.

A D Vanker, W Van Stoecker

    Computers and Biomedical Research, an International Journal
    |June 1, 1984
    PubMed
    Summary

    This study introduces the first AI-powered medical consultation program for dermatology, achieving 84% accuracy in diagnosing 13 skin tumors. It also features the first visually indexed dermatology database.

    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

    AI/COAG, a knowledge-based surrogate for the human hemostasis expert.

    Missouri medicine·1983
    Same author

    Changes in the activity of acetylcholinesterase from the brain of the Mongolian gerbil (Meriones unguiculatus) with age.

    Comparative biochemistry and physiology. C: Comparative pharmacology·1979
    Same author

    The mechanism of action of beta-bungarotoxin.

    Journal of neurochemistry·1975
    See all related articles

    Area of Science:

    • Dermatology
    • Artificial Intelligence
    • Medical Informatics

    Background:

    • Knowledge-based systems are emerging in medical diagnostics.
    • Dermatology diagnosis often relies on visual pattern recognition and expert knowledge.
    • Integrating computational methods can enhance diagnostic accuracy and accessibility.

    Purpose of the Study:

    • To report the development of the first knowledge-based medical consultation program for dermatology.
    • To introduce SEEK, a new facility within the Rutgers University EXPERT system, for medical consultation.
    • To present a visually indexed database for dermatological applications.

    Main Methods:

    • Developed a knowledge-based system utilizing a formal criteria-based knowledge representation scheme.
    • Integrated the SEEK facility within the Rutgers University EXPERT system.
    • Created the first visually indexed database specifically for dermatology.

    Main Results:

    • The developed model achieved an 84% overall accuracy in providing differential diagnoses for 13 different skin tumors.
    • Successfully implemented a novel knowledge representation scheme for medical data.
    • Established a functional visually indexed database for dermatological information.

    Conclusions:

    • The first knowledge-based medical consultation program for dermatology has been successfully developed and validated.
    • The SEEK system demonstrates significant potential in assisting dermatological diagnosis.
    • The visually indexed database represents a novel approach to managing dermatological information.

    Related Experiment Videos