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

Framework for quality assessment of knowledge.

J Brender1, J Talmon, P McNair

  • 1Medical Informatics Laboratory ApS, Lyngby, Denmark.

Studies in Health Technology and Informatics
|December 9, 1994
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

Response to the letter to the editor: "Prevalence and predictors of neglect-like symptoms in patients with painful hand osteoarthritis".

Musculoskeletal science & practice·2023
Same author

Development of a prediction model to determine responders to conservative treatment in people with symptomatic hand osteoarthritis: A secondary analysis of a single-centre, randomised feasibility trial.

Musculoskeletal science & practice·2022
Same author

Neglect-like symptoms and their relationships with other clinical features in people with hand osteoarthritis: An exploratory study.

Musculoskeletal science & practice·2022
Same author

Six weeks of resistance training (plus advice) vs advice only in hand osteoarthritis: A single-blind, randomised, controlled feasibility trial.

Musculoskeletal science & practice·2021
Same author

Improving Evaluation to Address the Unintended Consequences of Health Information Technology:. a Position Paper from the Working Group on Technology Assessment & Quality Development.

Yearbook of medical informatics·2016
Same author

Psychological rather than pharmacological interventions for effective prevetion of pain after knee joint replacement?

British journal of anaesthesia·2015
Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026
Same journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026
Same journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026
Same journal

Delay-Dependent Gating in Modular RNNs.

Studies in health technology and informatics·2026
See all related articles

Assessing the quality of medical knowledge, especially in knowledge-based systems (KBS), is crucial. This study introduces a framework to measure the semantic and pragmatic quality of knowledge within classification models during development.

Area of Science:

  • Medical Informatics
  • Knowledge Engineering
  • Machine Learning Evaluation

Background:

  • The effective application of medical knowledge, whether in knowledge-based systems (KBS) or other forms, hinges on rigorous quality assessment.
  • Evaluating the quality of embedded knowledge is a critical, yet often challenging, aspect of developing medical informatics tools.

Purpose of the Study:

  • To present a novel framework for managing and quantifying the quality of medical knowledge.
  • To address both the semantic (meaning) and pragmatic (usability) dimensions of knowledge quality.
  • To specifically target the development phase of classification models in medical applications.

Main Methods:

  • Development of a structured framework for knowledge quality assessment.
  • Implementation of measurable metrics for semantic knowledge aspects.

Related Experiment Videos

  • Implementation of measurable metrics for pragmatic knowledge aspects.
  • Integration of these metrics into the classification model development lifecycle.

    • Main Results:

    • The proposed framework enables systematic management of knowledge quality.
    • Semantic and pragmatic aspects of knowledge within classification models can be quantitatively assessed.
    • Measurable quality indicators are established for knowledge embedded in medical classification models.

    Conclusions:

    • The presented framework provides a robust approach to ensuring the quality of medical knowledge in classification models.
    • This methodology enhances the reliability and applicability of AI-driven medical knowledge systems.
    • Standardized quality assessment is essential for the trustworthy development and deployment of medical AI.