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

Investigation of Disease Outbreaks

Investigation of Disease Outbreaks

Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...

Steps in Outbreak Investigation

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:

Principles of Disease Surveillance

Principles of Disease Surveillance

Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...

Infectious Diseases and Their Occurrence

Infectious Diseases and Their Occurrence

Infectious diseases appear in populations through various transmission patterns, influenced by pathogen characteristics, population immunity, environmental conditions, and social behavior. Understanding these patterns is essential for effective public health surveillance and intervention. These categories—sporadic, outbreak, epidemic, pandemic, and endemic—help frame the nature and scope of disease events.Sporadic diseases occur irregularly and infrequently, without a predictable temporal or...

Classification of Illness

Classification of Illness

The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe and...

Causality in Epidemiology

Causality in Epidemiology

Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...

You might also read

Related Articles

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

Sort by

Same author

Global, Regional, and National Burden of Nontraumatic Subarachnoid Hemorrhage: The Global Burden of Disease Study 2021.

JAMA neurology·2025

Same author

Generative language models exhibit social identity biases.

Nature computational science·2024

Same author

Semantic Speech Networks Linked to Formal Thought Disorder in Early Psychosis.

Schizophrenia bulletin·2023

Same author

A survey on clinical natural language processing in the United Kingdom from 2007 to 2022.

NPJ digital medicine·2022

Same author

BioCaster in 2021: automatic disease outbreaks detection from global news media.

Bioinformatics (Oxford, England)·2022

Same author

Exploiting document graphs for inter sentence relation extraction.

Journal of biomedical semantics·2022

Search research articles

Related Experiment Video

Updated: Jul 5, 2026

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

Structuring an event ontology for disease outbreak detection.

Ai Kawazoe¹, Hutchatai Chanlekha, Mika Shigematsu

¹National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, 101-8430, Japan. zoeai@nii.ac.jp

BMC Bioinformatics

|May 9, 2008

Summary

This study introduces an event ontology to improve machine understanding of infectious disease events. It aids in early outbreak detection by linking public language to expert knowledge and enabling multilingual analysis.

More Related Videos

A Study on an Intelligent Diagnosis and Treatment Assistant System for Acupuncture in Diminished Ovarian Reserve Based on a Knowledge Graph

A Study on an Intelligent Diagnosis and Treatment Assistant System for Acupuncture in Diminished Ovarian Reserve Based on a Knowledge Graph

Published on: May 29, 2026

Related Experiment Videos

Last Updated: Jul 5, 2026

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

A Study on an Intelligent Diagnosis and Treatment Assistant System for Acupuncture in Diminished Ovarian Reserve Based on a Knowledge Graph

A Study on an Intelligent Diagnosis and Treatment Assistant System for Acupuncture in Diminished Ovarian Reserve Based on a Knowledge Graph

Published on: May 29, 2026

Area of Science:

Natural Language Processing
Ontology Engineering
Public Health Informatics

Background:

Developing an event ontology for machine understanding of infectious disease events.
Addressing the gap between layman's language and expert knowledge in disease outbreak reports.
Facilitating timely detection and assessment of disease outbreaks through multilingual information.

Purpose of the Study:

To design an event ontology for machine comprehension of infectious disease events.
To bridge the communication gap between the public and health experts.
To enable rapid assessment of disease outbreak alerting status.

Main Methods:

Integrating expert knowledge models for disease surveillance.
Incorporating linguistic expressions for disease-related events.
Structuring the ontology with general event classes at the upper level and specific events at the lower level.
Linking event classes with participants, multilingual synonym sets, and axioms.

Main Results:

The designed event ontology facilitates machine understanding of natural language text related to infectious diseases.
The ontology integrates expert knowledge with linguistic expressions and formal event definitions.
A hierarchical structure places general event classes at the top and specific expert-relevant events at the bottom.

Conclusions:

The event ontology design and methodology are applicable to other domains requiring natural language information integration.
Machine support for expert assessment of information is enhanced by this approach.
The first version of the ontology, containing approximately 40 concepts, is planned for release in March 2008.