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

Anatomical Terminology

Anatomical Terminology

Knowledge of anatomy is essential to understand human biology and medicine. Anatomists and health care professionals use standard terminology to describe the human body with more precision and no ambiguity. Anatomical terms have mostly Greek and Latin-derived roots. Because these languages are rarely used in conversation, the meaning of words remains the same. Each term is made up of a root in between the prefixes and suffixes. The root of a term often refers to an organ, tissue, or condition,...

Genome Annotation and Assembly

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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

Toward Real-World Reproducibility: Verifying Value Sets for Clinical Research.

Studies in health technology and informatics·2024

Same author

Developing a sampling method and preliminary taxonomy for classifying COVID-19 public health guidance for healthcare organizations and the general public.

Journal of biomedical informatics·2021

Same author

Development of a Process and Infrastructure to Outreach Stakeholders for Capturing Healthcare System Stress in Emergency Response Situations.

Online journal of public health informatics·2019

Same author

Risperdal<sup>®</sup> CONSTA<sup>®</sup> Needle Detachment. Incidence Rates Before and After Kit Redesign: A Retrospective Study using Electronic Health Records and Natural Language Processing in the Department of Veterans Affairs.

Neurology and therapy·2019

Same author

Identifying Patients With Relapsing-Remitting Multiple Sclerosis Using Algorithms Applied to US Integrated Delivery Network Healthcare Data.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research·2019

Same author

Gap Analysis and Refinement Recommendations of Skin Alteration and Pressure Ulcer Enterprise Reference Models against Nursing Flowsheet Data Elements.

AMIA ... Annual Symposium proceedings. AMIA Symposium·2018

Search research articles

Related Experiment Video

Updated: Jul 2, 2026

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

Building knowledge: a system for batch loading biomedical terminologies.

Aaron W C Kamauu¹, Jeff D Scadden, Ronald O Lenk

¹RemedyMD Inc, Sandy, Utah, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium

|August 13, 2008

Summary

This summary is machine-generated.

Developing efficient methods for biomedical ontologies is crucial for healthcare applications. A new system enables the simultaneous loading of numerous terminology concepts, improving ontology robustness and supporting diverse healthcare needs.

More Related Videos

A Web Tool for Generating High Quality Machine-readable Biological Pathways

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

Related Experiment Videos

Last Updated: Jul 2, 2026

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

A Web Tool for Generating High Quality Machine-readable Biological Pathways

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

Area of Science:

Biomedical Informatics
Knowledge Representation
Health Informatics

Background:

Biomedical ontologies are essential for supporting healthcare applications by organizing vast amounts of terminology.
Traditional methods for loading concepts into these ontologies are often inefficient and labor-intensive.
The complexity and scale of biomedical data necessitate improved ontology management techniques.

Purpose of the Study:

To develop an efficient system for loading a large number of terminology concepts into biomedical ontologies.
To enhance the robustness and scalability of biomedical ontologies.
To facilitate the application of comprehensive ontologies in various healthcare domains.

Main Methods:

Development of a novel system designed for the simultaneous ingestion of multiple terminology concepts.
Implementation of automated or semi-automated processes to streamline the loading procedure.
Testing the system's capacity to handle a large volume of standard and proprietary biomedical terms.

Main Results:

Successful development of a system capable of simultaneously loading a large volume of terminology concepts.
Demonstration of improved efficiency compared to conventional labor-intensive loading methods.
Creation of a more robust and comprehensive biomedical ontology.

Conclusions:

The developed system offers a more efficient and scalable solution for populating biomedical ontologies.
Robust biomedical ontologies are critical for advancing various health care applications.
This approach addresses the limitations of traditional methods, paving the way for enhanced knowledge management in healthcare.