TCCC Decision Support With Machine Learning Prediction of Hemorrhage Risk, Shock Probability
Abstract
Expected future delays in evacuation during near-peer conflicts in remote locales are expected to require extended care including prolonged field care over hours to days. Such delays can increase potential complications, such as insufficient blood flow (shock), bloodstream infection (sepsis), internal bleeding (hemorrhage), and require more complex treatment beyond stabilization. The Trauma Triage Treatment and Training Decision Support (4TDS) system is a real-time decision support system to monitor casualty health and identify such complications. The 4TDS software prototype operates on an Android smart phone or tablet configured for use in the DoD Nett Warrior program. It includes machine learning models to evaluate trends in six vital signs streamed from a sensor placed on a casualty to identify shock probability, internal hemorrhage risk, and need for a massive transfusion.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Nov 01, 2023
- Source ID
- 10.1093/milmed/usad298
Entities
People
- Adam Amos-binks
- Christopher Nemeth
- Dawn Laufersweiler
- Gregory Rule
- Isaac Flint
- Natalie Keeney
- Vitaly Herasevich
- Yuliya Pinevich
Organizations
- Applied Research Associates (United States)
- Mayo Clinic
- United States Army Medical Research and Development Command