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Rendering knowledge graphs from aerospace dentistry processes for clinical decision support systems.

Muhammad Tuan Amith1,2, Jessica Vu3, Serena Hou4

  • 1Department of Biostatistics and Data Science, University of Texas Medical Branch, 301 University Blvd, Galveston, 77555, TX, USA.

Acta Astronautica
|December 19, 2025
PubMed
Summary
This summary is machine-generated.

This study models aerospace dental workflows for deep space missions using Business Process Modeling and Notation (BPMN) and OWL2 knowledge graphs. These computable models support remote clinical decision-making for astronaut dental care.

Keywords:
Aerospace dentistryDental emergenciesHealth informaticsKnowledge graphsOntologyProcess modeling

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Area of Science:

  • Aerospace Medicine
  • Health Informatics
  • Computational Dentistry

Background:

  • Long-term space missions necessitate robust healthcare solutions for astronauts.
  • Limited crew and equipment in deep space pose challenges for clinical procedures.
  • Standardized workflows are crucial for ensuring astronaut safety and quality care.

Purpose of the Study:

  • To develop and represent aerospace dental workflows for space missions.
  • To utilize Business Process Modeling and Notation (BPMN) and OWL2 for modeling.
  • To create computable knowledge graphs for dental procedures in space.

Main Methods:

  • Developed BPMN process models for aerospace dental workflows.
  • Created ontology-based knowledge graphs using OWL2.
  • Employed a semi-automated processing pipeline for model development.
  • Generated knowledge graphs for specific dental conditions: abscess, extractions, dislodged restorations, and trauma.

Main Results:

  • Four OWL2-based knowledge graphs were produced, detailing semantic descriptions of key dental procedures.
  • The models represent individual dental procedures for low-earth orbit and deep space missions.
  • The knowledge graphs are computable, enabling integration into software applications.

Conclusions:

  • The developed OWL2 knowledge graphs provide a foundation for decision support systems in space.
  • These models can enhance remote clinical tools for astronaut dental care.
  • Future work includes expanding the knowledge graphs and developing applications for space healthcare.