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Ontologic Model of Diagnostics and Treatment of Gastrointestinal Bleedings of Unknown Origin

Anna Budykina1, Svetlana Rauzina1, Alexander Bogdanov1

  • 1N.I. Pirogov Russia National Research Medical University, Moscow.

Studies in Health Technology and Informatics
|July 27, 2019
PubMed

Insights

This study introduces a semantic model for diagnosing and treating gastrointestinal bleeding when standard tests fail. It aids clinicians in managing complex cases of obscure gastrointestinal bleeding.

Area of Science:

  • Gastroenterology
  • Medical Informatics
  • Clinical Diagnostics

Background:

  • Gastrointestinal bleeding (GIB) poses significant diagnostic challenges, particularly when initial investigations are inconclusive.
  • Obscure GIB often requires advanced diagnostic and treatment strategies beyond standard laboratory tests, endoscopy, and colonoscopy.

Purpose of the Study:

  • To develop and present a semantic model for the diagnostics and treatment of patients with gastrointestinal bleedings.
  • To provide a structured approach for managing GIB cases where the bleeding source remains unidentified after conventional methods.

Main Methods:

  • Development of a semantic model integrating clinical data, diagnostic pathways, and treatment options.
  • Application of the model to analyze and categorize complex GIB cases.

Main Results:

  • The semantic model offers a framework for systematic evaluation and management of obscure GIB.
  • Facilitates identification of potential diagnostic and therapeutic strategies tailored to individual patient profiles.

Conclusions:

  • The proposed semantic model enhances the diagnostic and therapeutic capabilities for managing challenging gastrointestinal bleeding cases.
  • It represents a valuable tool for clinicians facing unexplained GIB, improving patient care pathways.

Keywords:
CDSSDBMSGI bleedingSBB.clinical decision support systemsclinical guidelinesdatabase management systemgastrointestinal bleedingontologysmall-bowel bleeding

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