Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Health Information Technology and Healthcare Information System

Health Information Technology and Healthcare Information System

Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:

You might also read

Related Articles

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

Sort by

Same author

Intelligent contributions of the artificial orca algorithm for continuous problems and real-time emergency medical services.

Evolutionary intelligence·2023

Same author

A decomposition-based multiobjective evolutionary algorithm using Simulated Annealing for the ambulance dispatching and relocation problem during COVID-19.

Applied soft computing·2023

Same author

Quantum OPTICS and deep self-learning on swarm intelligence algorithms for Covid-19 emergency transportation.

Soft computing·2022

Same author

Bat-Inspired Algorithm Based Query Expansion for Medical Web Information Retrieval.

Journal of medical systems·2017

Same journal

Starmate: A Lightweight AI Assistant for Autism Caregivers Developed and Evaluated Through a User-Centered Mixed-Methods Framework.

Journal of medical systems·2026

Same journal

Predicting the Predictor: Unresolved Validity Threats in LLM-Based ASA Classification.

Journal of medical systems·2026

Same journal

Development and Internal Validation of a Vectorcardiography-Augmented Model for 12-Month Major Adverse Cardiovascular Events in Chronic Heart Failure.

Journal of medical systems·2026

Same journal

Development and Validation of an Automated Acute Kidney Injury E-Alert System Integrated with Clinical Decision Support for Hospitalized Patients.

Journal of medical systems·2026

Same journal

Calibration of Self-Reported Confidence and Accuracy of Large Language Models in Medical Question Answering.

Journal of medical systems·2026

Same journal

Throughput Benchmarking and Throughput Variance Analysis to Evaluate the Efficiency of an Outpatient Endoscopy Unit.

Journal of medical systems·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 2, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

A Firefly Algorithm-based Approach for Pseudo-Relevance Feedback: Application to Medical Database.

Ilyes Khennak¹, Habiba Drias²

¹Laboratory for Research in Artificial Intelligence, Computer Science Department, USTHB, BP 32 El Alia, 16111, Bab Ezzouar, Algiers, Algeria. ikhennak@usthb.dz.

Journal of Medical Systems

|September 29, 2016

Summary

This summary is machine-generated.

This study introduces a novel Firefly Algorithm for query expansion, improving search engine accuracy by adding relevant keywords. The method enhances information retrieval effectiveness with low computational cost.

Keywords:

Firefly Algorithm MEDLINE Medical data management Pseudo-relevance feedback Query expansion Swarm intelligence Web intelligence

More Related Videos

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Related Experiment Videos

Last Updated: Jul 2, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Area of Science:

Information Retrieval
Computer Science
Artificial Intelligence

Background:

Search queries often use imprecise keywords, leading to retrieval failures.
Query expansion is a key method to improve search engine performance by augmenting original queries.

Purpose of the Study:

To propose a new Firefly Algorithm-based approach for query expansion.
To enhance retrieval effectiveness and maintain low computational complexity.

Main Methods:

Utilized a Firefly Algorithm to select the optimal expanded query from candidate sets.
Determined the expanded query length empirically.
Evaluated the approach on the MEDLINE database.

Main Results:

The proposed Firefly Algorithm approach demonstrated superior effectiveness compared to existing methods.
The approach proved more efficient than state-of-the-art techniques.

Conclusions:

The Firefly Algorithm is effective for query expansion in information retrieval.
This method offers an efficient way to improve search engine performance and user satisfaction.