Exploitation of Bayesian Networks for Clinical Decision Support on the Battlefield

Abstract

The purpose of this research is to optimize the care of battlefield trauma patients through the development of Bayesian-network (BN) machine learning-powered clinical decision-support (CDS) tools. Scope: The scope of the research encompasses the refinement of existing BNs, and development and prototyping of new BNs designed for pre-hospital, en-route, and deployed healthcare facility stages of care, such that CDS prototypes are available for piloting and assessment in future, real-world clinical studies. Major Findings Year 3 Data. Permissions and access to UK Joint Theatre Trauma Registry Transfusion Dataset gained (needed for building transfusion model) and access to US Joint Theatre Trauma System gained (needed for external validation of model set) achieved. UK Human Research Authority permission gained for Decision Support end user use-ability studies.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2022
Accession Number
AD1190940

Entities

People

  • Nigel Tai

Organizations

  • Queen Mary University of London

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Bayesian Networks
  • Blood
  • Blood Transfusions
  • Bone Fractures
  • Brain Injuries
  • Combat Injuries
  • Computational Science
  • Computers
  • Health Services
  • Hospitals
  • Machine Learning
  • Medical Personnel
  • Military Medicine
  • Predictive Modeling
  • Students
  • Therapy
  • User Interface

Readers

  • Clinical Trial Research.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.
  • Trauma or Military Medicine

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy