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 Concept Videos

Mesh Analysis01:20

Mesh Analysis

Mesh analysis is a valuable method for simplifying circuit analysis using mesh currents as key circuit variables. Unlike nodal analysis, which focuses on determining unknown voltages, mesh analysis applies Kirchhoff's voltage law (KVL) to find unknown currents within a circuit. This method is particularly convenient in reducing the number of simultaneous equations that need to be solved.
A fundamental concept in mesh analysis is the definition of meshes and mesh currents. A mesh is a closed...

You might also read

Related Articles

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

Sort by
Same journal

Medical code embeddings from claims-based co-occurrences: a unified semantic space for ICD-10 diagnoses and ATC medications.

Journal of the American Medical Informatics Association : JAMIA·2026
Same journal

Translating machine learning predictions into meaningful risk estimates to support clinical decisions: a post hoc analysis of chronic obstructive pulmonary disease adverse outcomes using unified auto clinical scores.

Journal of the American Medical Informatics Association : JAMIA·2026
Same journal

Integrating human and artificial intelligence for robust postmarketing safety surveillance systems: reflections from the FDA Sentinel Innovation Center.

Journal of the American Medical Informatics Association : JAMIA·2026
Same journal

PDA (Privacy-Preserving Distributed Algorithms) in action: ten principles for high-quality multi-site clinical evidence generation.

Journal of the American Medical Informatics Association : JAMIA·2026
Same journal

Reporting follow-up budgets for diagnostic and predictive AI.

Journal of the American Medical Informatics Association : JAMIA·2026
Same journal

Digital divide in clinical and operational artificial intelligence adoption and implementation stages: US hospital diffusion patterns and AI deserts.

Journal of the American Medical Informatics Association : JAMIA·2026

Related Experiment Video

Updated: May 18, 2026

Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands
10:59

Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands

Published on: July 26, 2014

Improving image retrieval effectiveness via query expansion using MeSH hierarchical structure.

Mariano Crespo Azcárate1, Jacinto Mata Vázquez, Manuel Maña López

  • 1Department of Information Technology, University of Huelva, Huelva, Spain.

Journal of the American Medical Informatics Association : JAMIA
|September 7, 2012
PubMed
Summary

Query expansion using Medical Subject Headings (MeSH) improved medical image retrieval. Both tested strategies enhanced performance, with one winning the 2011 ImageCLEF task by significantly boosting mean average precision (MAP).

More Related Videos

Multimodal Hierarchical Imaging of Serial Sections for Finding Specific Cellular Targets within Large Volumes
11:19

Multimodal Hierarchical Imaging of Serial Sections for Finding Specific Cellular Targets within Large Volumes

Published on: March 20, 2018

Related Experiment Videos

Last Updated: May 18, 2026

Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands
10:59

Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands

Published on: July 26, 2014

Multimodal Hierarchical Imaging of Serial Sections for Finding Specific Cellular Targets within Large Volumes
11:19

Multimodal Hierarchical Imaging of Serial Sections for Finding Specific Cellular Targets within Large Volumes

Published on: March 20, 2018

Area of Science:

  • Medical Informatics
  • Information Retrieval
  • Biomedical Imaging

Background:

  • Medical image retrieval systems often face challenges with query effectiveness.
  • Improving search accuracy is crucial for efficient access to medical visual data.
  • Medical Subject Headings (MeSH) ontology offers a structured vocabulary for medical concepts.

Purpose of the Study:

  • To investigate two query expansion strategies using MeSH ontology to enhance medical image retrieval.
  • To identify terms within search queries most suitable for expansion.
  • To evaluate the impact of MeSH-based query expansion on retrieval system performance.

Main Methods:

  • Utilized the hierarchical structure of MeSH descriptors for query expansion.
  • Implemented two strategies: 1) expanding based on Unified Medical Language System (UMLS) metathesaurus concepts, and 2) expanding based on n-grams of query text mapped to MeSH descriptors.
  • Evaluated performance using the ImageCLEF 2011 medical image retrieval dataset and Mean Average Precision (MAP).

Main Results:

  • Both query expansion strategies surpassed the average MAP score of the ImageCLEF 2011 competition (0.1644).
  • The n-gram expansion strategy achieved a MAP of 0.2004 (21.89% improvement).
  • The medical concepts expansion strategy achieved a MAP of 0.2172 (32.11% improvement), winning the text-based retrieval task.

Conclusions:

  • Query expansion leveraging the hierarchical structure of MeSH descriptors significantly improves medical image retrieval system effectiveness.
  • The medical concepts expansion strategy demonstrated superior performance in enhancing retrieval accuracy.
  • This approach offers a robust method for optimizing medical image search.