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

Supporting medical decisions with vector decision trees.

M Sprogar1, P Kokol, M Zorman

  • 1Laboratory for system design, Faculty of electrical engineering and computer science, University of Maribor, SI-2000 Maribor, Slovenia. matej.sprogar@uni-mb.si

Studies in Health Technology and Informatics
|October 18, 2001
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

Bone marrow-derived stromal cells are associated with gastric cancer progression.

British journal of cancer·2015
Same author

Accuracy of intelligent medical systems.

Computer methods and programs in biomedicine·2006
Same author

Sex differences in mucosal response to Helicobacter pylori infection in the stomach and variations in interleukin-8, COX-2 and trefoil factor family 1 gene expression.

Alimentary pharmacology & therapeutics·2004
Same author

Diagnostic value of culture, histology and PCR for Helicobacter pylori in the remnant stomach after surgery.

Alimentary pharmacology & therapeutics·2004
Same author

Masticatory performance with a prosthesis following maxillectomy: an analysis of 43 cases.

Journal of oral rehabilitation·2003
Same author

Molecular characterization of Cryptosporidium isolates obtained from human and bovine infections in Japan.

Parasitology research·2001
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

This study introduces the vector decision tree, an evolutionary computing-based extension of traditional decision trees. This novel approach offers enhanced decision-making capabilities by providing multiple suggestions per input sample.

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Machine Learning

Background:

  • Traditional decision trees offer single suggestions per input.
  • Complex decision-making processes often require multiple outputs.
  • Existing methods may obscure relationships between different decisions.

Purpose of the Study:

  • To extend the concept of decision trees to a multidimensional vector decision tree.
  • To explore the capabilities of vector decision trees using evolutionary techniques.
  • To develop a software tool for building and testing vector decision trees.

Main Methods:

  • Construction of multidimensional vector decision trees using evolutionary techniques.
  • Development of the DecRain software tool for building vector decision trees.

Related Experiment Videos

  • Comparative analysis of vector decision trees against classical decision trees.

    • Main Results:

    • Vector decision trees can provide multiple suggestions per input sample.
    • The DecRain tool effectively builds vector decision trees.
    • Generated vector decision trees demonstrated strong performance compared to classical decision trees.
    • Vector decision trees reveal previously hidden relationships between decisions.

    Conclusions:

    • Vector decision trees are a powerful extension of traditional decision trees.
    • The concept is applicable to a wide range of decision-making processes.
    • Vector decision trees offer a simple, analyzable, and effective approach to complex problems.