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Related Concept Videos

Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Methods of Documentation VI: Case Management Model

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Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases
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Published on: March 19, 2018

Health care ontologies: knowledge models for record sharing and decision support.

Maria Madsen1

  • 1School of Management and Information Systems, Central Queensland University, Rockhampton Qld and eHealth Education Pty Ltd. m.madsen@ehealtheducation.net

Studies in Health Technology and Informatics
|April 22, 2010
PubMed
Summary
This summary is machine-generated.

This chapter explains formal ontologies, detailing their design objectives like re-use and interoperability. It highlights how formal ontologies enhance semantic interoperability and support intelligent decision support systems.

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Last Updated: Jun 13, 2026

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases
07:26

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

Area of Science:

  • Computer Science
  • Information Science
  • Artificial Intelligence

Background:

  • Ontologies are crucial for organizing knowledge.
  • Distinguishing between informal and formal ontologies is essential for effective knowledge representation.

Purpose of the Study:

  • To provide an educational overview of formal ontologies.
  • To elucidate the objectives and applications of ontology design.
  • To demonstrate the role of ontologies in enhancing semantic interoperability and decision support.

Main Methods:

  • Conceptual overview of ontology design principles.
  • Explanation of terminology mapping and classification systems.
  • Discussion of ontology re-use, extensibility, and interoperability.

Main Results:

  • Formal ontologies offer superior structure and expressiveness compared to informal ones.
  • Formal ontologies facilitate the mapping of diverse terminologies and classification systems.
  • Well-formed ontologies are foundational for developing intelligent decision support systems.

Conclusions:

  • Formal ontologies are key to achieving semantic interoperability.
  • Effective ontology design promotes re-use, extensibility, and interoperability.
  • Ontologies significantly advance the capabilities of intelligent decision support.